diff --git a/chdb/__main__.py b/chdb/__main__.py index eaf164c24eb..28f73669120 100644 --- a/chdb/__main__.py +++ b/chdb/__main__.py @@ -21,11 +21,14 @@ def main(): sql = options.sql[0] output_format = options.format res = query(sql, output_format) - if output_format.lower() in ('dataframe', 'arrowtable'): - temp = res - else: - temp = res.data() - print(temp, end="") + try: + if output_format.lower() in ("dataframe", "arrowtable"): + temp = res + else: + temp = res.data() + print(temp, end="") + except UnicodeDecodeError: + print(repr(res.bytes())) if __name__ == '__main__': diff --git a/chdb/build.sh b/chdb/build.sh index a19fea2d1bc..c288e435326 100755 --- a/chdb/build.sh +++ b/chdb/build.sh @@ -90,7 +90,7 @@ CMAKE_ARGS="-DCMAKE_BUILD_TYPE=${build_type} -DENABLE_THINLTO=0 -DENABLE_TESTS=0 -DENABLE_UTILS=0 ${LLVM} ${UNWIND} \ ${ICU} -DENABLE_UTF8PROC=1 ${JEMALLOC} \ -DENABLE_PARQUET=1 -DENABLE_ROCKSDB=1 -DENABLE_SQLITE=1 -DENABLE_VECTORSCAN=1 \ - -DENABLE_PROTOBUF=1 -DENABLE_THRIFT=1 \ + -DENABLE_PROTOBUF=1 -DENABLE_THRIFT=1 -DENABLE_MSGPACK=1 \ -DENABLE_RAPIDJSON=1 \ -DENABLE_BROTLI=1 -DENABLE_H3=1 \ -DENABLE_CLICKHOUSE_ALL=0 -DUSE_STATIC_LIBRARIES=1 -DSPLIT_SHARED_LIBRARIES=0 \ diff --git a/programs/local/LocalChdb.cpp b/programs/local/LocalChdb.cpp index f52acbc1d91..e8ce0617632 100644 --- a/programs/local/LocalChdb.cpp +++ b/programs/local/LocalChdb.cpp @@ -38,6 +38,7 @@ local_result_v2 * queryToBuffer( // Add path string argv.push_back("--path=" + path); } + // argv.push_back("--no-system-tables"); // Add query string argv.push_back("--query=" + queryStr); diff --git a/programs/local/LocalServer.cpp b/programs/local/LocalServer.cpp index 99a4366d0e0..4c900be18ab 100644 --- a/programs/local/LocalServer.cpp +++ b/programs/local/LocalServer.cpp @@ -1050,10 +1050,14 @@ class query_result_ }; +// global mutex for all local servers +static std::mutex CHDB_MUTEX; + std::unique_ptr pyEntryClickHouseLocal(int argc, char ** argv) { try { + std::lock_guard lock(CHDB_MUTEX); DB::LocalServer app; app.init(argc, argv); int ret = app.run(); diff --git a/src/Common/PythonUtils.cpp b/src/Common/PythonUtils.cpp index 266772ff66d..c402d915524 100644 --- a/src/Common/PythonUtils.cpp +++ b/src/Common/PythonUtils.cpp @@ -1,3 +1,4 @@ +#include #include #include "config.h" @@ -6,10 +7,10 @@ #include #include #include - -#include -#include +#include #include +#include +#include namespace DB { @@ -122,13 +123,40 @@ ConvertPyUnicodeToUtf8(const void * input, int kind, size_t codepoint_cnt, Colum return offset; // Return the number of bytes written, not including the null terminator } +int PyString_AsStringAndSize(PyObject * ob, char ** charpp, Py_ssize_t * sizep) +{ + // always convert it to utf8, but this case is rare, here goes the slow path + py::gil_scoped_acquire acquire; + if (PyUnicode_Check(ob)) + { + *charpp = const_cast(PyUnicode_AsUTF8AndSize(ob, sizep)); + if (*charpp == nullptr) + { + return -1; + } + return 0; + } + else + { + return PyBytes_AsStringAndSize(ob, charpp, sizep); + } +} + void FillColumnString(PyObject * obj, ColumnString * column) { ColumnString::Offsets & offsets = column->getOffsets(); ColumnString::Chars & chars = column->getChars(); + // if obj is bytes + // if (PyBytes_Check(obj)) + // { + // // convert bytes to string + // column->insertData(data, bytes_size); + // } + // else if (PyUnicode_IS_COMPACT_ASCII(obj)) { - const char * data = reinterpret_cast(PyUnicode_1BYTE_DATA(obj)); + // if obj is unicode + const char * data = reinterpret_cast(PyUnicode_DATA(obj)); size_t unicode_len = PyUnicode_GET_LENGTH(obj); column->insertData(data, unicode_len); } @@ -160,10 +188,10 @@ void FillColumnString(PyObject * obj, ColumnString * column) } else { - // always convert it to utf8, but this case is rare, here goes the slow path - py::gil_scoped_acquire acquire; Py_ssize_t bytes_size = -1; - const char * data = PyUnicode_AsUTF8AndSize(obj, &bytes_size); + // const char * data = PyUnicode_AsUTF8AndSize(obj, &bytes_size); + char * data = nullptr; + bytes_size = PyString_AsStringAndSize(obj, &data, &bytes_size); if (bytes_size < 0) throw Exception(ErrorCodes::PY_EXCEPTION_OCCURED, "Failed to convert Python unicode object to UTF-8"); column->insertData(data, bytes_size); @@ -266,7 +294,7 @@ bool _isInheritsFromPyReader(const py::handle & obj) // Will try to get the ref of py::array from pandas Series, or PyArrow Table // without import numpy or pyarrow. Just from class name for now. -const void * tryGetPyArray(const py::object & obj, py::handle & result, std::string & type_name, size_t & row_count) +const void * tryGetPyArray(const py::object & obj, py::handle & result, py::handle & tmp, std::string & type_name, size_t & row_count) { py::gil_scoped_acquire acquire; type_name = py::str(obj.attr("__class__").attr("__name__")).cast(); @@ -283,6 +311,28 @@ const void * tryGetPyArray(const py::object & obj, py::handle & result, std::str // Try to get the handle of py::array from pandas Series py::array array = obj.attr("values"); row_count = py::len(obj); + // if element type is bytes or object, we need to convert it to string + // chdb todo: need more type check + if (row_count > 0) + { + auto elem_type = obj.attr("__getitem__")(0).attr("__class__").attr("__name__").cast(); + if (elem_type == "str" || elem_type == "unicode") + { + result = array; + return array.data(); + } + if (elem_type == "bytes" || elem_type == "object") + { + // chdb todo: better handle for bytes and object type + auto str_obj = obj.attr("astype")(py::dtype("str")); + array = str_obj.attr("values"); + result = array; + tmp = array; + tmp.inc_ref(); + return array.data(); + } + } + result = array; return array.data(); } diff --git a/src/Common/PythonUtils.h b/src/Common/PythonUtils.h index 75d6b00f8a3..2e24ebc7f21 100644 --- a/src/Common/PythonUtils.h +++ b/src/Common/PythonUtils.h @@ -30,11 +30,21 @@ struct ColumnWrapper void * buf; // we may modify the data when cast it to PyObject **, so we need a non-const pointer size_t row_count; py::handle data; + py::handle tmp; // hold some tmp data like hits['Title'].astype("str") DataTypePtr dest_type; std::string py_type; //py::handle type, eg. numpy.ndarray; std::string row_format; std::string encoding; // utf8, utf16, utf32, etc. std::string name; + + ~ColumnWrapper() + { + py::gil_scoped_acquire acquire; + if (!tmp.is_none()) + { + tmp.dec_ref(); + } + } }; using PyObjectVec = std::vector; @@ -194,7 +204,7 @@ inline std::vector readData(const py::object & data_source, const st return execWithGIL([&]() { return data_source.attr("read")(names, cursor, count).cast>(); }); } -const void * tryGetPyArray(const py::object & obj, py::handle & result, std::string & type_name, size_t & row_count); +const void * tryGetPyArray(const py::object & obj, py::handle & result, py::handle & tmp, std::string & type_name, size_t & row_count); } // namespace DB #endif diff --git a/src/Processors/Sources/PythonSource.cpp b/src/Processors/Sources/PythonSource.cpp index 786f8348d20..3543777eff5 100644 --- a/src/Processors/Sources/PythonSource.cpp +++ b/src/Processors/Sources/PythonSource.cpp @@ -1,4 +1,5 @@ #include +#include "base/scope_guard.h" #if USE_PYTHON #include @@ -147,7 +148,12 @@ ColumnPtr PythonSource::convert_and_insert(const py::object & obj, UInt32 scale) std::string type_name; size_t row_count; py::handle py_array; - const void * data = tryGetPyArray(obj, py_array, type_name, row_count); + py::handle tmp; + SCOPE_EXIT({ + if (!tmp.is_none()) + tmp.dec_ref(); + }); + const void * data = tryGetPyArray(obj, py_array, tmp, type_name, row_count); if (!py_array.is_none()) { if constexpr (std::is_same_v) @@ -416,19 +422,38 @@ Chunk PythonSource::generate() if (names.empty()) return {}; - if (isInheritsFromPyReader(data_source)) + try { - PyObjectVecPtr data; - py::gil_scoped_acquire acquire; - data = std::move(castToSharedPtrVector(data_source.attr("read")(names, max_block_size))); - if (data->empty()) - return {}; + if (isInheritsFromPyReader(data_source)) + { + PyObjectVecPtr data; + py::gil_scoped_acquire acquire; + data = std::move(castToSharedPtrVector(data_source.attr("read")(names, max_block_size))); + if (data->empty()) + return {}; - return std::move(genChunk(num_rows, data)); + return std::move(genChunk(num_rows, data)); + } + else + { + return std::move(scanDataToChunk()); + } } - else + catch (const Exception & e) + { + throw Exception(ErrorCodes::PY_EXCEPTION_OCCURED, "Python data handling {}", e.what()); + } + catch (const std::exception & e) + { + throw Exception(ErrorCodes::PY_EXCEPTION_OCCURED, "Python data handling {}", e.what()); + } + catch (const py::error_already_set & e) + { + throw Exception(ErrorCodes::PY_EXCEPTION_OCCURED, "Python data handling {}", e.what()); + } + catch (...) { - return std::move(scanDataToChunk()); + throw Exception(ErrorCodes::PY_EXCEPTION_OCCURED, "Python data handling unknown exception"); } } } diff --git a/src/Storages/MergeTree/MergeTreeBackgroundExecutor.cpp b/src/Storages/MergeTree/MergeTreeBackgroundExecutor.cpp index c78788d921a..16236a07962 100644 --- a/src/Storages/MergeTree/MergeTreeBackgroundExecutor.cpp +++ b/src/Storages/MergeTree/MergeTreeBackgroundExecutor.cpp @@ -151,7 +151,10 @@ void printExceptionWithRespectToAbort(LoggerPtr log, const String & query_id) if (ex == nullptr) return; - tryLogCurrentException(log, "Exception while executing background task {" + query_id + "}"); + NOEXCEPT_SCOPE({ + ALLOW_ALLOCATIONS_IN_SCOPE; + tryLogCurrentException(log, "Exception while executing background task {" + query_id + "}"); + }); // try // { // std::rethrow_exception(ex); diff --git a/src/Storages/StoragePython.cpp b/src/Storages/StoragePython.cpp index 8a65484d774..ce02b956f9f 100644 --- a/src/Storages/StoragePython.cpp +++ b/src/Storages/StoragePython.cpp @@ -110,7 +110,7 @@ void StoragePython::prepareColumnCache(const Names & names, const Columns & colu try { py::object col_data = data_source[py::str(col_name)]; - col.buf = const_cast(tryGetPyArray(col_data, col.data, col.py_type, col.row_count)); + col.buf = const_cast(tryGetPyArray(col_data, col.data, col.tmp, col.py_type, col.row_count)); if (col.buf == nullptr) throw Exception( ErrorCodes::PY_EXCEPTION_OCCURED, "Convert to array failed for column {} type {}", col_name, col.py_type); diff --git a/tests/arrow_table.py b/tests/arrow_table.py index 66663b1fc2a..5f97cbf9f5f 100644 --- a/tests/arrow_table.py +++ b/tests/arrow_table.py @@ -4,6 +4,7 @@ import time import chdb import chdb.dataframe as cdf +import chdb.session as chs import pandas as pd import numpy as np import pyarrow as pa @@ -37,6 +38,8 @@ sql = "SELECT COUNT(DISTINCT UserID) FROM hits;" +# sql = "SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\.)?([^/]+)/.*$', '\1') AS k, AVG(STRLEN(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;" + t = time.time() # read parquet file into memory with open(hits_0, "rb") as f: @@ -65,6 +68,8 @@ # # hits[col] = hits[col].astype('string') # hits[col] = hits[col].astype(str) +hits["Referer"] = hits["Referer"].astype(str) + # title = hits["Title"] # title.values.data @@ -216,17 +221,22 @@ def read(self, col_names, count): reader = myReader(df_old) +sess = chs.Session() +# sess.query("set aggregation_memory_efficient_merge_threads=2;") + +sql = sql.replace("STRLEN", "length") def bench_chdb(i): if i == 0: format = "Debug" else: format = "DataFrame" - ret = chdb.query( + ret = sess.query( # """ SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) # FROM Python(reader) GROUP BY RegionID ORDER BY c DESC LIMIT 10""", # "SELECT COUNT(DISTINCT Title) FROM Python(reader);", - sql.replace("hits", "Python(hits)"), + "set aggregation_memory_efficient_merge_threads=3;" + + sql.replace("hits", "Python(hits)"), format, ) return ret diff --git a/tests/pd_zerocopy.ipynb b/tests/pd_zerocopy.ipynb index 2e3e480f00f..314e43a939b 100644 --- a/tests/pd_zerocopy.ipynb +++ b/tests/pd_zerocopy.ipynb @@ -9,56 +9,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "Name: duckdb\n", - "Version: 0.10.1\n", - "Summary: DuckDB in-process database\n", - "Home-page: https://www.duckdb.org\n", - "Author: None\n", - "Author-email: None\n", - "License: MIT\n", - "Location: /usr/local/lib/python3.9/dist-packages\n", - "Requires: \n", - "Required-by: \n", - "Name: pandas\n", - "Version: 2.2.1\n", - "Summary: Powerful data structures for data analysis, time series, and statistics\n", - "Home-page: https://pandas.pydata.org\n", - "Author: None\n", - "Author-email: The Pandas Development Team \n", - "License: BSD 3-Clause License\n", - " \n", - " Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team\n", - " All rights reserved.\n", - " \n", - " Copyright (c) 2011-2023, Open source contributors.\n", - " \n", - " Redistribution and use in source and binary forms, with or without\n", - " modification, are permitted provided that the following conditions are met:\n", - " \n", - " * Redistributions of source code must retain the above copyright notice, this\n", - " list of conditions and the following disclaimer.\n", - " \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " this list of conditions and the following disclaimer in the documentation\n", - " and/or other materials provided with the distribution.\n", - " \n", - " * Neither the name of the copyright holder nor the names of its\n", - " contributors may be used to endorse or promote products derived from\n", - " this software without specific prior written permission.\n", - " \n", - " THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\n", - " DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\n", - " FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\n", - " DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\n", - " SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\n", - " CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\n", - " OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\n", - " OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n", - "Location: /usr/local/lib/python3.9/dist-packages\n", - "Requires: tzdata, pytz, python-dateutil, numpy\n", - "Required-by: fastparquet\n", + "Requirement already satisfied: duckdb in /usr/local/lib/python3.9/dist-packages (1.0.0)\n", + "Collecting duckdb\n", + " Using cached duckdb-1.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.5 MB)\n", + " Using cached duckdb-0.10.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.5 MB)\n", + "Requirement already satisfied: pandas in /usr/local/lib/python3.9/dist-packages (2.2.2)\n", + "Collecting pandas\n", + " Using cached pandas-2.2.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.1 MB)\n", + " Using cached pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB)\n", + "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.9/dist-packages (from pandas) (1.24.2)\n", + "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.9/dist-packages (from pandas) (2023.3)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.9/dist-packages (from pandas) (2.8.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7)\n", + "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n", "Name: chdb\n", "Version: 1.3.0\n", "Summary: chDB is an in-process SQL OLAP Engine powered by ClickHouse\n", @@ -73,8 +36,8 @@ } ], "source": [ - "!pip show duckdb\n", - "!pip show pandas\n", + "!pip install -U duckdb\n", + "!pip install -U pandas\n", "!pip show chdb" ] }, @@ -87,9 +50,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Read parquet file into memory. Time cost: 0.6527159214019775 s\n", + "Read parquet file into memory. Time cost: 0.7327933311462402 s\n", "Parquet file size: 1395695970 bytes\n", - "Read parquet file as old pandas dataframe. Time cost: 9.359078884124756 s\n", + "Read parquet file as old pandas dataframe. Time cost: 9.861586093902588 s\n", "Dataframe(numpy) size: 4700000128 bytes\n" ] } @@ -250,7 +213,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Convert old dataframe to numpy array. Time cost: 9.179115295410156e-05 s\n" + "Convert old dataframe to numpy array. Time cost: 9.751319885253906e-05 s\n" ] } ], @@ -342,26 +305,27 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "counter = 0\n", "\n", - "sess = chs.Session()\n", - "sess.query(\"set aggregation_memory_efficient_merge_threads=4;\")\n", "\n", "def runDuckDB(con, sql):\n", + " used_time = -1\n", " try:\n", " t = time.time()\n", " ret = con.execute(sql).fetch_df()\n", " used_time = time.time() - t\n", + " print(\"DuckDB time:\", used_time)\n", " print(\"DuckDB return:\\n\", ret)\n", " except Exception as e:\n", " print(\"DuckDB error:\", e)\n", " return used_time\n", "\n", "def runChDB(sess, sql):\n", + " used_time = -1\n", " # replace 'hits' with 'Python(df_reader)'\n", " sql = sql.replace(\"hits\", \"Python(hits)\")\n", " # sql = sql.replace(\"hits\", \"__hits__\")\n", @@ -370,8 +334,9 @@ " sql = \"SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM Python(hits) WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000\"\n", " try:\n", " t = time.time()\n", - " ret = sess.query(sql, \"CSV\")\n", + " ret = chdb.query(sql, \"CSV\")\n", " used_time = time.time() - t\n", + " print(\"chDB time:\", used_time)\n", " print(\"chDB return:\\n\", ret)\n", " except Exception as e:\n", " print(\"chDB error:\", e)\n", @@ -386,14 +351,14 @@ " print(\"Q\"+str(counter)+\":\", sql)\n", " for i in range(1):\n", " duckdb_time.append(runDuckDB(con, sql))\n", - " chdb_time.append(runChDB(sess, sql))\n", + " chdb_time.append(runChDB(None, sql))\n", " counter += 1\n", " return duckdb_time, chdb_time" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -401,55 +366,70 @@ "output_type": "stream", "text": [ "Q0: SELECT COUNT(*) FROM hits;\n", + "DuckDB time: 0.03776884078979492\n", "DuckDB return:\n", " count_star()\n", "0 10000000\n", + "chDB time: 0.0594487190246582\n", "chDB return:\n", " 10000000\n", "\n", "Q1: SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;\n", + "DuckDB time: 0.06189227104187012\n", "DuckDB return:\n", " count_star()\n", "0 257266\n", + "chDB time: 0.03596901893615723\n", "chDB return:\n", " 257266\n", "\n", "Q2: SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;\n", + "DuckDB time: 0.027609825134277344\n", "DuckDB return:\n", " sum(AdvEngineID) count_star() avg(ResolutionWidth)\n", "0 5276263.0 10000000 1506.781497\n", + "chDB time: 0.0348505973815918\n", "chDB return:\n", " 5276263,10000000,1506.7814968\n", "\n", "Q3: SELECT AVG(UserID) FROM hits;\n", + "DuckDB time: 0.023339509963989258\n", "DuckDB return:\n", " avg(UserID)\n", "0 2.302915e+18\n", + "chDB time: 0.032269954681396484\n", "chDB return:\n", " -152254684228.51132\n", "\n", "Q4: SELECT COUNT(DISTINCT UserID) FROM hits;\n", + "DuckDB time: 0.07855987548828125\n", "DuckDB return:\n", " count(DISTINCT UserID)\n", "0 1620177\n", + "chDB time: 0.09619355201721191\n", "chDB return:\n", " 1620177\n", "\n", "Q5: SELECT COUNT(DISTINCT SearchPhrase) FROM hits;\n", + "DuckDB time: 0.1246495246887207\n", "DuckDB return:\n", " count(DISTINCT SearchPhrase)\n", "0 873731\n", + "chDB time: 0.2143714427947998\n", "chDB return:\n", " 873731\n", "\n", "Q6: SELECT MIN(EventDate), MAX(EventDate) FROM hits;\n", + "DuckDB time: 0.03154158592224121\n", "DuckDB return:\n", " min(EventDate) max(EventDate)\n", "0 2013-07-02 2013-07-31\n", + "chDB time: 0.04444766044616699\n", "chDB return:\n", " \"2013-07-02 08:00:00.000000000\",\"2013-07-31 08:00:00.000000000\"\n", "\n", "Q7: SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;\n", + "DuckDB time: 0.04121232032775879\n", "DuckDB return:\n", " AdvEngineID count_star()\n", "0 27 107474\n", @@ -462,6 +442,7 @@ "7 52 34\n", "8 3 9\n", "9 28 8\n", + "chDB time: 0.0443270206451416\n", "chDB return:\n", " 27,107474\n", "2,94688\n", @@ -475,6 +456,7 @@ "28,8\n", "\n", "Q8: SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.08478951454162598\n", "DuckDB return:\n", " RegionID u\n", "0 229 289257\n", @@ -487,6 +469,7 @@ "7 107 26996\n", "8 42 26944\n", "9 32 26577\n", + "chDB time: 0.09266400337219238\n", "chDB return:\n", " 229,289257\n", "2,114971\n", @@ -500,6 +483,7 @@ "32,26577\n", "\n", "Q9: SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.10983133316040039\n", "DuckDB return:\n", " RegionID sum(AdvEngineID) c avg(ResolutionWidth) \\\n", "0 229 1626324.0 2031299 1553.786671 \n", @@ -524,6 +508,7 @@ "7 33622 \n", "8 17202 \n", "9 20111 \n", + "chDB time: 0.09492039680480957\n", "chDB return:\n", " 229,1626324,2031299,1553.7866714846018,289257\n", "2,313589,877397,1423.5402149768006,114971\n", @@ -537,6 +522,7 @@ "36,53042,141420,1588.640758025739,20111\n", "\n", "Q10: SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.0515902042388916\n", "DuckDB return:\n", " MobilePhoneModel u\n", "0 iPad 80774\n", @@ -549,6 +535,7 @@ "7 GT-P7300B 139\n", "8 GT-I9500 131\n", "9 eagle75 131\n", + "chDB time: 0.11583352088928223\n", "chDB return:\n", " \"iPad\",80774\n", "\"iPhone\",3568\n", @@ -562,6 +549,7 @@ "\"GT-I9500\",131\n", "\n", "Q11: SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.06019878387451172\n", "DuckDB return:\n", " MobilePhone MobilePhoneModel u\n", "0 1 iPad 68519\n", @@ -574,6 +562,7 @@ "7 10 iPad 965\n", "8 13 iPad 770\n", "9 32 iPad 746\n", + "chDB time: 0.1006321907043457\n", "chDB return:\n", " 1,\"iPad\",68519\n", "5,\"iPad\",3788\n", @@ -587,6 +576,7 @@ "32,\"iPad\",746\n", "\n", "Q12: SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.13083744049072266\n", "DuckDB return:\n", " SearchPhrase c\n", "0 ведомосквы вместу 4947\n", @@ -599,6 +589,7 @@ "7 отдых в кино 1272\n", "8 тачки рецепт собстве 1248\n", "9 рецепты сбербан 1244\n", + "chDB time: 0.16352367401123047\n", "chDB return:\n", " \"ведомосквы вместу\",4947\n", "\"смотреть онлайн бесплатно\",3338\n", @@ -612,6 +603,7 @@ "\"рецепты сбербан\",1244\n", "\n", "Q13: SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;\n", + "DuckDB time: 0.1800699234008789\n", "DuckDB return:\n", " SearchPhrase u\n", "0 смотреть онлайн бесплатно 2717\n", @@ -624,6 +616,7 @@ "7 смотреть онлайн бесплатно в хорошем 953\n", "8 рецепты сбербан 909\n", "9 ф-1 894\n", + "chDB time: 0.10894894599914551\n", "chDB return:\n", " \"смотреть онлайн бесплатно\",2717\n", "\"смотреть онлайн\",2085\n", @@ -637,6 +630,7 @@ "\"ф-1\",894\n", "\n", "Q14: SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.1431279182434082\n", "DuckDB return:\n", " SearchEngineID SearchPhrase c\n", "0 2 ведомосквы вместу 3480\n", @@ -649,6 +643,7 @@ "7 2 люкс 20 иномаровск 1257\n", "8 2 рецепты сбербан 1172\n", "9 4 покеты рецепт засня 959\n", + "chDB time: 0.14469361305236816\n", "chDB return:\n", " 2,\"ведомосквы вместу\",3480\n", "2,\"смотреть онлайн бесплатно\",2194\n", @@ -662,6 +657,7 @@ "4,\"покеты рецепт засня\",959\n", "\n", "Q15: SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;\n", + "DuckDB time: 0.07811951637268066\n", "DuckDB return:\n", " UserID count_star()\n", "0 1313338681122956954 29097\n", @@ -674,6 +670,7 @@ "7 517714522250745823 2119\n", "8 6762020047108358913 2051\n", "9 6718662516719813769 1678\n", + "chDB time: 0.08990716934204102\n", "chDB return:\n", " 1313338681122956954,29097\n", "1907779576417363396,16854\n", @@ -687,6 +684,7 @@ "6718662516719813769,1678\n", "\n", "Q16: SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", + "DuckDB time: 0.16716980934143066\n", "DuckDB return:\n", " UserID SearchPhrase count_star()\n", "0 1313338681122956954 29097\n", @@ -699,6 +697,7 @@ "7 517714522250745823 2119\n", "8 6762020047108358913 2051\n", "9 6718662516719813769 1651\n", + "chDB time: 0.15459275245666504\n", "chDB return:\n", " 1313338681122956954,\"\",29097\n", "1907779576417363396,\"\",16854\n", @@ -712,18 +711,20 @@ "6718662516719813769,\"\",1651\n", "\n", "Q17: SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;\n", + "DuckDB time: 0.15761113166809082\n", "DuckDB return:\n", - " UserID SearchPhrase count_star()\n", - "0 1148203358839991043 безвизорах книга ребенка 1\n", - "1 1149188038666898517 люкс инство франчаж 1\n", - "2 1150421916676073475 20\n", - "3 1151034831649949995 4\n", - "4 1151735951084394604 люкс и фекалка 320 plus 1\n", - "5 1153089247952456010 35\n", - "6 1155336989347633766 санатория валерия смотража 1\n", - "7 1156129693689106990 фото иогам сироп 1\n", - "8 1156438049345202882 3\n", - "9 1156460196963222616 погода в паренье 3\n", + " UserID SearchPhrase count_star()\n", + "0 1036083730235124430 6\n", + "1 1036164594836748969 люксор цены 2\n", + "2 1036173074041401450 38\n", + "3 1036264744294437707 2\n", + "4 1036277947224996319 53\n", + "5 1036356465395350033 1\n", + "6 1036458158923935276 1\n", + "7 1036478553297069811 3\n", + "8 1036490651249159646 1\n", + "9 1036490651249159646 смешарики нет магазин в хорошем 1\n", + "chDB time: 0.14002585411071777\n", "chDB return:\n", " 119657425828985633,\"\",1\n", "301536536637670246,\"люкс eob 33 сезон\",1\n", @@ -737,6 +738,7 @@ "676440968882228424,\"маша табло\",1\n", "\n", "Q18: SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;\n", + "DuckDB time: 0.21877121925354004\n", "DuckDB return:\n", " UserID m SearchPhrase count_star()\n", "0 1313338681122956954 31 589\n", @@ -749,6 +751,7 @@ "7 1313338681122956954 34 546\n", "8 1313338681122956954 26 540\n", "9 1313338681122956954 10 539\n", + "chDB time: 0.20485448837280273\n", "chDB return:\n", " 1313338681122956954,31,\"\",589\n", "1313338681122956954,28,\"\",578\n", @@ -762,44 +765,50 @@ "1313338681122956954,10,\"\",539\n", "\n", "Q19: SELECT UserID FROM hits WHERE UserID = 435090932899640449;\n", + "DuckDB time: 0.039788007736206055\n", "DuckDB return:\n", " Empty DataFrame\n", "Columns: [UserID]\n", "Index: []\n", + "chDB time: 0.049802541732788086\n", "chDB return:\n", " \n", "Q20: SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';\n", + "DuckDB time: 0.09707260131835938\n", "DuckDB return:\n", " count_star()\n", "0 621\n", + "chDB time: 0.20763850212097168\n", "chDB return:\n", " 621\n", "\n", "Q21: SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.1250753402709961\n", "DuckDB return:\n", " SearchPhrase \\\n", - "0 один инструктура птахани нюши смотреть краси \n", - "1 зачать онлайн бесплатно \n", - "2 ани пух ходу \n", - "3 как миксетин инструкция общая \n", - "4 комбактерина кабачки в крополь интерном сад тю... \n", - "5 строитель верси джейкоциты вычета \n", - "6 скачать денег сургут \n", - "7 михайловар для андроизводские новок \n", - "8 сделатья длиннотика б \n", - "9 монить какое озера \n", + "0 строитель верси джейкоциты вычета \n", + "1 комбактерина кабачки в крополь интерном сад тю... \n", + "2 зачать онлайн бесплатно \n", + "3 ани пух ходу \n", + "4 один инструктура птахани нюши смотреть краси \n", + "5 как миксетин инструкция общая \n", + "6 пансии \n", + "7 стоянного телефонны для семейн \n", + "8 онкой областинны кристрии медведь \n", + "9 турбо мультратить в установка \n", "\n", " min(URL) c \n", - "0 http://bdsm_position/2624217,2013-07-01:2013/f... 2 \n", - "1 http://tienskaia-moda-brietielkakh-2%2F%2Fwww.... 2 \n", - "2 http://interinburg/detail.google,yandex.aspx#l... 2 \n", - "3 http://samara.irr.ru/catalog_googleMBR%26ad%3D... 2 \n", - "4 http://samara.irr.ru/catalog_googleTBR%26ad%3D... 2 \n", - "5 http://ru.tv/smsarhiv/num-9/nf-3/csrf-39818/go... 2 \n", - "6 http://tienskaia-moda-brietielka-koskovsk/deta... 1 \n", - "7 http://psyche.html?1=1&cid=577&oki=1&option=Ju... 1 \n", - "8 http://tienskaia-moda-brietielkakh-2%2F%2Fwww.... 1 \n", - "9 http://auto.ria.ua/auto_id=0&order=False&minpr... 1 \n", + "0 http://ru.tv/smsarhiv/num-9/nf-3/csrf-39818/go... 2 \n", + "1 http://samara.irr.ru/catalog_googleTBR%26ad%3D... 2 \n", + "2 http://tienskaia-moda-brietielkakh-2%2F%2Fwww.... 2 \n", + "3 http://interinburg/detail.google,yandex.aspx#l... 2 \n", + "4 http://bdsm_position/2624217,2013-07-01:2013/f... 2 \n", + "5 http://samara.irr.ru/catalog_googleMBR%26ad%3D... 2 \n", + "6 http://samara.irr.ru/catalog_googleMBR%26ad%3D... 1 \n", + "7 http://tienskaia-moda-brietielkakh%2F&sr=http:... 1 \n", + "8 http://teratorage.aspx?naId=8664210990/guests/... 1 \n", + "9 http://wildberries.ru/cgi-bin/novosibirsk/deta... 1 \n", + "chDB time: 0.134476900100708\n", "chDB return:\n", " \"ани пух ходу\",\"http://interinburg/detail.google,yandex.aspx#location=products\",2\n", "\"комбактерина кабачки в крополь интерном сад тюмень\",\"http://samara.irr.ru/catalog_googleTBR%26ad%3D278885%26bt%3D430001216\",2\n", @@ -813,6 +822,7 @@ "\"скачать денег сургут\",\"http://tienskaia-moda-brietielka-koskovsk/detail.google\",1\n", "\n", "Q22: SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.22784948348999023\n", "DuckDB return:\n", " SearchPhrase \\\n", "0 коптимиквиды юриста с роуз рая \n", @@ -821,9 +831,9 @@ "3 заделать магнездо \n", "4 вспомидоры,отека обучение стека \n", "5 авторы для jimm f/4-5.6 dc union arkham текст \n", - "6 создать+новосибируюсь песни летние \n", - "7 коптимизаностиницы \n", - "8 вспышки нижний эльдар \n", + "6 коптимизаностиницы \n", + "7 вспышки нижний эльдар \n", + "8 создать+новосибируюсь песни летние \n", "9 ведомосквиталия страции \n", "\n", " min(URL) \\\n", @@ -833,9 +843,9 @@ "3 http://auto.ria.ua/search/ab_district=1&cid=57... \n", "4 https://produkty%2Fpulove.ru/booklyattion-war-... \n", "5 http://nn.jobinmoscow.ru/real-estate/rent/Sroc... \n", - "6 http://auto.ria.ua/search/ab_district=1&cid=57... \n", - "7 https://produkty%2Fpulove.ru/booklyattion-war-... \n", - "8 http://mysw.info/newsru.ru/compatible \n", + "6 https://produkty%2Fpulove.ru/booklyattion-war-... \n", + "7 http://mysw.info/newsru.ru/compatible \n", + "8 http://auto.ria.ua/search/ab_district=1&cid=57... \n", "9 https://produkty%2Fpulove.ru/booklyattion-war-... \n", "\n", " min(Title) c \\\n", @@ -845,9 +855,9 @@ "3 AUTO.ria.ua: продажа | Востов-на-Дону, чашечка... 13 \n", "4 Легко на участные участников., Цены - Стильная... 10 \n", "5 Google Papa Rapalace Rescu - модной тканика Ас... 9 \n", - "6 AUTO.ria.ua: продажа | Востов-на-Дону, чашечка... 8 \n", - "7 Легко на участные участников., Цены - Стильная... 8 \n", - "8 Convent-менеджер с Google Players 1.3 кв. м.- ... 8 \n", + "6 Легко на участные участников., Цены - Стильная... 8 \n", + "7 Convent-менеджер с Google Players 1.3 кв. м.- ... 8 \n", + "8 AUTO.ria.ua: продажа | Востов-на-Дону, чашечка... 8 \n", "9 Легко на участные участников., Цены - Стильная... 8 \n", "\n", " count(DISTINCT UserID) \n", @@ -857,10 +867,11 @@ "3 13 \n", "4 1 \n", "5 9 \n", - "6 1 \n", - "7 2 \n", - "8 6 \n", + "6 2 \n", + "7 6 \n", + "8 1 \n", "9 3 \n", + "chDB time: 0.25702500343322754\n", "chDB return:\n", " \"коптимиквиды юриста с роуз рая\",\"https://produkty%2Fpulove.ru/booklyattion-war-sinij-9182/women\",\"Легко на участные участников., Цены - Стильная парнем. Саганрог догадения : Турции, купить у 10 дне кольные машинки не представки - Новая с избиение спродажа: котята 2014 г.в. Цена: 47500-10ECO060 – -------- купить квартиру Оренбург (России Galantrax Flamiliada Google, Nо 18 фотоконверк Супер Кардиган\",45,12\n", "\"ведомосквы вместу\",\"http://mysw.info/newsru.ru/compatible\",\"Convent-менеджер с Google Players 1.3 кв. м.- Продажа: лет - купить Bisbal Systеms Aparty*\",17,11\n", @@ -874,6 +885,7 @@ "\"создать+новосибируюсь песни летние\",\"http://auto.ria.ua/search/ab_district=1&cid=577&action&op\",\"AUTO.ria.ua: продажа | Востов-на-Дону, чашечка Google Cayennection Polo | б.у. и новых. Автопоиска и купить в Омск - IRR.ru - Роддово, ул. Гибочной день цене\",8,1\n", "\n", "Q23: SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;\n", + "DuckDB time: 0.40861058235168457\n", "DuckDB return:\n", " WatchID JavaEnable \\\n", "0 7316105502961799889 1 \n", @@ -936,6 +948,7 @@ "9 0 662346848875253897 -5547551342880266035 0 \n", "\n", "[10 rows x 105 columns]\n", + "chDB time: 0.5413117408752441\n", "chDB return:\n", " 7316105502961799889,1,\"Аренда 2 игры для женщин в интернет-магазин - bonprix.ru#imaged Jacobs\",1,\"2013-07-02 05:27:24.000000000\",\"2013-07-02 08:00:00.000000000\",7525,1419090217,229,3033510353420765788,1,126,7,\"http://sp-money.yandex.ru%2Fkategory_name=Плагроув&where=all&filmId=WNkeCKQOeSs&where=all&text=песню актика googleuser=trading/page3/?auth=0&checked_auto.ria.ua/advizhi/price_do=600&wi=1024&wi=1440%26rnd%3D158197%26bt%3Dad.adriver.ru/filmId=HjCfhSXPbEY&where=all&filmId=dgV5JJuhk3E&where\",\"http://bdsmpeople.ru&network=vk&refereriGvhiKo7lw&bvm=bv.48705608\",0,12895,158,12132,216,1087,938,23,15,2,\"700.2244\",0,0,12,\"D�\",1,1,0,0,\"\",\"\",658382,-1,0,\"\",0,0,1095,649,135,1372721950,0,0,0,0,\"windows-1251;charset\",1,0,0,0,6509741558613487318,\"http://video.yandex.by/search/price_highlight%253Dhttp://rmnt.ru/search?text=%D1%80%D0%BC%20%D1%83%D0%BB%D0%B5%D0%B8%D1%80%D0%BF%D0%BA%D0%A2%D0%B3%D1%83%D0%B0%D0%BE%D0%B8%D0%B7%D0%BB%D1%83%D0%BB%D0%BD%D0%BB%D0%B0%D0%BD%D0%BC%D0%B8%D0%B5%20%D0%BB%D1%82%D1%87%D0%B5%D0%B8%20%E4%E0%E1%EE%ED%ED%F1%F2%F0%F2%FB%E9+%E3%E8%F1%F2%F0%E8%ED%E0+%D0%B8%D0%BE%20%D1%82%D1%80%D0%B0%D1%82%D1%8F%20with_photo=¤cy=RUR&is_hot=0&vip=0&op_style_id=2097775%2C257&pvno=2&evlg=VC,2;VL,248;IC,16;VL\",1022450989,0,0,0,0,0,\"5\",1372786972,0,1,3,6,66,1818130458,-1,-1,-1,\"S0\",\"h1\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,-7095314016616002272,-2039922795398915081,0\n", "5289360038140010777,1,\"Инвеста.Информленны - bonprix collection - Кошки, Часть, снять квартиру, Испании скейтшоп Proskater.ru (Работка сноубордовищ\",1,\"2013-07-02 07:02:43.000000000\",\"2013-07-02 08:00:00.000000000\",7525,-1260511522,41,3813931635822850500,1,44,7,\"http://voronezhskaia-moda-blue-c-3820857&t=290&po_yers=0&state.google.ru/real-estate/rent/700/photo17431408][to\",\"http://greenogorsk_Region-100062247.137505%26xpid\",0,12895,158,12132,216,1638,1658,23,15,2,\"700.169\",0,0,12,\"D�\",1,1,0,0,\"\",\"\",1835209,-1,0,\"\",0,0,1369,1018,135,1372711247,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,8229313317592864677,\"\",975298214,0,0,0,0,0,\"5\",1372717306,50,2,3,16292,0,-673048140,-1,-1,-1,\"S0\",\"h1\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,8622994845783504296,441678500069920832,0\n", @@ -949,18 +962,20 @@ "6405590155111045434,1,\"Инвеста.Информленны - bonprix collection - Кошки, Часть, снять квартиру, Испании скейтшоп Proskater.ru (Работка сноубордовищ\",1,\"2013-07-02 07:07:33.000000000\",\"2013-07-02 08:00:00.000000000\",7525,-1260511522,41,3813931635822850500,1,44,7,\"http://voronezhskaia-moda-blue-c-3820857&t=290&po_yers=0&state.google.ru/real-estate/out-of-town/land.web-3.ru\",\"http://greenogorsk_Region-100062247.137438\",0,12895,158,12132,216,1638,1658,23,15,2,\"700.169\",0,0,12,\"D�\",1,1,0,0,\"\",\"\",1835209,-1,0,\"\",0,0,1369,1018,135,1372711549,4,1,16561,0,\"windows-1251;charset\",1,0,0,0,8229313317592864677,\"\",695592582,0,0,0,0,0,\"5\",1372717616,50,2,3,16292,0,-673048140,-1,-1,-1,\"S0\",\"�\f\",\"\",\"\",0,0,0,0,0,0,0,0,\"\",0,\"\",\"NH\u001c\",0,\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",\"\",0,662346848875253897,-5547551342880266035,0\n", "\n", "Q24: SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;\n", + "DuckDB time: 0.12740063667297363\n", "DuckDB return:\n", " SearchPhrase\n", - "0 симптомы регистратов\n", - "1 ночно китая женщины\n", + "0 ночно китая женщины\n", + "1 симптомы регистратов\n", "2 отдыха чем прокат\n", "3 скачать читалию в духовке\n", "4 купить ваз 2121099 инжира 1 сезон смотреть онл...\n", "5 маршава нибудь в омске главнованные автобаза ф...\n", "6 вакансионал 28 неделю вытяжного печь бабка бу ...\n", "7 венгридический якутии видео ни\n", - "8 санандроид малининец фармарин\n", - "9 0б1 купить в парня смотреть онлайн\n", + "8 0б1 купить без програма\n", + "9 санандроид малининец фармарин\n", + "chDB time: 0.08882927894592285\n", "chDB return:\n", " \"ночно китая женщины\"\n", "\"симптомы регистратов\"\n", @@ -974,6 +989,7 @@ "\"санандроид малининец фармарин\"\n", "\n", "Q25: SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;\n", + "DuckDB time: 0.22864127159118652\n", "DuckDB return:\n", " SearchPhrase\n", "0 светы женске 2 сезон\n", @@ -986,6 +1002,7 @@ "7 $_postarshippuden paris stan\n", "8 $d причина\n", "9 $d причина\n", + "chDB time: 0.06814384460449219\n", "chDB return:\n", " \" светы женске 2 сезон\"\n", "\"! hektdf gjcgjhn conster\"\n", @@ -999,6 +1016,7 @@ "\"$d причина\"\n", "\n", "Q26: SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;\n", + "DuckDB time: 0.2071990966796875\n", "DuckDB return:\n", " SearchPhrase\n", "0 ночно китая женщины\n", @@ -1011,6 +1029,7 @@ "7 венгридический якутии видео ни\n", "8 0б1 купить без програма\n", "9 0б1 купить в парня смотреть онлайн\n", + "chDB time: 0.08399128913879395\n", "chDB return:\n", " \"ночно китая женщины\"\n", "\"симптомы регистратов\"\n", @@ -1024,6 +1043,7 @@ "\"0б1 купить в парня смотреть онлайн\"\n", "\n", "Q27: SELECT CounterID, AVG(STRLEN(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", + "DuckDB time: 0.11247992515563965\n", "DuckDB return:\n", " CounterID l c\n", "0 1634 198.148049 315442\n", @@ -1041,6 +1061,7 @@ "12 5822 62.768687 383161\n", "13 1060 61.041178 252489\n", "14 7525 58.612668 584968\n", + "chDB time: 0.17406105995178223\n", "chDB return:\n", " 1634,198.14804940369388,315442\n", "786,186.7507135271472,120528\n", @@ -1059,13 +1080,16 @@ "7525,58.61266770148111,584968\n", "\n", "Q28: SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\\.)?([^/]+)/.*$', '\u0001') AS k, AVG(STRLEN(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;\n", + "DuckDB time: 0.19605565071105957\n", "DuckDB return:\n", " k l c min(Referer)\n", "0 \u0001 99.401568 7697804 http://%26ad%3D1%260.html&ei=9e71d2f0b6590/3/w...\n", + "chDB time: 0.3529047966003418\n", "chDB return:\n", " \"\u0001\",99.40156803161005,7697804,\"http://%26ad%3D1%260.html&ei=9e71d2f0b6590/3/women.aspx?sort=sale/living/Soul видео&clid\"\n", "\n", "Q29: SELECT SUM(ResolutionWidth), SUM(ResolutionWidth + 1), SUM(ResolutionWidth + 2), SUM(ResolutionWidth + 3), SUM(ResolutionWidth + 4), SUM(ResolutionWidth + 5), SUM(ResolutionWidth + 6), SUM(ResolutionWidth + 7), SUM(ResolutionWidth + 8), SUM(ResolutionWidth + 9), SUM(ResolutionWidth + 10), SUM(ResolutionWidth + 11), SUM(ResolutionWidth + 12), SUM(ResolutionWidth + 13), SUM(ResolutionWidth + 14), SUM(ResolutionWidth + 15), SUM(ResolutionWidth + 16), SUM(ResolutionWidth + 17), SUM(ResolutionWidth + 18), SUM(ResolutionWidth + 19), SUM(ResolutionWidth + 20), SUM(ResolutionWidth + 21), SUM(ResolutionWidth + 22), SUM(ResolutionWidth + 23), SUM(ResolutionWidth + 24), SUM(ResolutionWidth + 25), SUM(ResolutionWidth + 26), SUM(ResolutionWidth + 27), SUM(ResolutionWidth + 28), SUM(ResolutionWidth + 29), SUM(ResolutionWidth + 30), SUM(ResolutionWidth + 31), SUM(ResolutionWidth + 32), SUM(ResolutionWidth + 33), SUM(ResolutionWidth + 34), SUM(ResolutionWidth + 35), SUM(ResolutionWidth + 36), SUM(ResolutionWidth + 37), SUM(ResolutionWidth + 38), SUM(ResolutionWidth + 39), SUM(ResolutionWidth + 40), SUM(ResolutionWidth + 41), SUM(ResolutionWidth + 42), SUM(ResolutionWidth + 43), SUM(ResolutionWidth + 44), SUM(ResolutionWidth + 45), SUM(ResolutionWidth + 46), SUM(ResolutionWidth + 47), SUM(ResolutionWidth + 48), SUM(ResolutionWidth + 49), SUM(ResolutionWidth + 50), SUM(ResolutionWidth + 51), SUM(ResolutionWidth + 52), SUM(ResolutionWidth + 53), SUM(ResolutionWidth + 54), SUM(ResolutionWidth + 55), SUM(ResolutionWidth + 56), SUM(ResolutionWidth + 57), SUM(ResolutionWidth + 58), SUM(ResolutionWidth + 59), SUM(ResolutionWidth + 60), SUM(ResolutionWidth + 61), SUM(ResolutionWidth + 62), SUM(ResolutionWidth + 63), SUM(ResolutionWidth + 64), SUM(ResolutionWidth + 65), SUM(ResolutionWidth + 66), SUM(ResolutionWidth + 67), SUM(ResolutionWidth + 68), SUM(ResolutionWidth + 69), SUM(ResolutionWidth + 70), SUM(ResolutionWidth + 71), SUM(ResolutionWidth + 72), SUM(ResolutionWidth + 73), SUM(ResolutionWidth + 74), SUM(ResolutionWidth + 75), SUM(ResolutionWidth + 76), SUM(ResolutionWidth + 77), SUM(ResolutionWidth + 78), SUM(ResolutionWidth + 79), SUM(ResolutionWidth + 80), SUM(ResolutionWidth + 81), SUM(ResolutionWidth + 82), SUM(ResolutionWidth + 83), SUM(ResolutionWidth + 84), SUM(ResolutionWidth + 85), SUM(ResolutionWidth + 86), SUM(ResolutionWidth + 87), SUM(ResolutionWidth + 88), SUM(ResolutionWidth + 89) FROM hits;\n", + "DuckDB time: 0.21096515655517578\n", "DuckDB return:\n", " sum(ResolutionWidth) sum((ResolutionWidth + 1)) \\\n", "0 1.506781e+10 1.507781e+10 \n", @@ -1098,10 +1122,12 @@ "0 1.594781e+10 1.595781e+10 \n", "\n", "[1 rows x 90 columns]\n", + "chDB time: 0.04774832725524902\n", "chDB return:\n", " 15067814968,15077814968,15087814968,15097814968,15107814968,15117814968,15127814968,15137814968,15147814968,15157814968,15167814968,15177814968,15187814968,15197814968,15207814968,15217814968,15227814968,15237814968,15247814968,15257814968,15267814968,15277814968,15287814968,15297814968,15307814968,15317814968,15327814968,15337814968,15347814968,15357814968,15367814968,15377814968,15387814968,15397814968,15407814968,15417814968,15427814968,15437814968,15447814968,15457814968,15467814968,15477814968,15487814968,15497814968,15507814968,15517814968,15527814968,15537814968,15547814968,15557814968,15567814968,15577814968,15587814968,15597814968,15607814968,15617814968,15627814968,15637814968,15647814968,15657814968,15667814968,15677814968,15687814968,15697814968,15707814968,15717814968,15727814968,15737814968,15747814968,15757814968,15767814968,15777814968,15787814968,15797814968,15807814968,15817814968,15827814968,15837814968,15847814968,15857814968,15867814968,15877814968,15887814968,15897814968,15907814968,15917814968,15927814968,15937814968,15947814968,15957814968\n", "\n", "Q30: SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.10490155220031738\n", "DuckDB return:\n", " SearchEngineID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", "0 2 -1262139876 189 14.0 1560.063492\n", @@ -1113,7 +1139,8 @@ "6 2 2145233773 151 25.0 1578.662252\n", "7 2 -792059583 148 10.0 1683.074324\n", "8 2 -1993532306 145 6.0 1625.655172\n", - "9 95 2031325834 138 1.0 1368.000000\n", + "9 2 -1945757555 138 9.0 1580.253623\n", + "chDB time: 0.08729386329650879\n", "chDB return:\n", " 2,-1262139876,189,14,1560.063492063492\n", "2,-927025522,187,26,1621.3689839572191\n", @@ -1127,43 +1154,47 @@ "2,-1945757555,138,9,1580.2536231884058\n", "\n", "Q31: SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.1439218521118164\n", "DuckDB return:\n", " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", - "0 5706109618028055866 -1779797105 1 0.0 1368.0\n", - "1 8956912881330537471 1979188611 1 0.0 1638.0\n", - "2 6841077450566933982 -1468947423 1 1.0 1638.0\n", - "3 8650116948197099994 -1355138210 1 1.0 1368.0\n", - "4 5016557349883925130 1526691792 1 0.0 2425.0\n", - "5 9043311828616509895 120716376 1 0.0 1638.0\n", - "6 7345595118662831258 -415862653 1 1.0 1996.0\n", - "7 8827783962121888333 -328542917 1 0.0 1368.0\n", - "8 6981660486621960995 1967440805 1 1.0 1990.0\n", - "9 6833279963723816774 1967440805 1 1.0 1990.0\n", + "0 7850017867931483391 632028542 1 0.0 1368.0\n", + "1 6026660848219330913 -520266432 1 0.0 1917.0\n", + "2 7782294289665804695 -575713225 1 0.0 1087.0\n", + "3 6736379209987461615 -575713225 1 1.0 1087.0\n", + "4 5871899583683104645 -575713225 1 1.0 1087.0\n", + "5 6742757367750688621 -739657338 1 1.0 661.0\n", + "6 6080400631029876822 2076458693 1 0.0 1921.0\n", + "7 7782079596197538435 -1465720169 1 0.0 1917.0\n", + "8 5394970432844081863 -1394170745 1 1.0 1917.0\n", + "9 9162069805174153037 1268901408 1 1.0 1996.0\n", + "chDB time: 0.11986732482910156\n", "chDB return:\n", - " 6427115150554230793,736252994,1,0,1996\n", + " 5494909287200572026,1492278923,1,0,1828\n", "4965054029390764634,-1206595968,1,0,166\n", "6030703977865133751,434911724,1,0,1996\n", "6691203620596311846,2003800917,1,0,1087\n", "5786133618012580033,1390766629,1,0,1368\n", "5985454501189037066,1832002778,1,0,1638\n", - "5494909287200572026,1492278923,1,0,1828\n", + "6829606353031419075,1926497591,1,0,1917\n", "8745161824300249528,1528045946,1,1,1638\n", "4698453950679016700,-1916962470,1,0,1750\n", "7352065519984549840,1557735347,1,0,1638\n", "\n", "Q32: SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.2230682373046875\n", "DuckDB return:\n", " WatchID ClientIP c sum(IsRefresh) avg(ResolutionWidth)\n", - "0 8799634747254053528 1594749084 1 0.0 1087.0\n", - "1 6373012662729354909 1940407723 1 0.0 1368.0\n", - "2 4743059398968615234 -1111685825 1 0.0 1996.0\n", - "3 8913409339414472893 747790483 1 0.0 1917.0\n", - "4 5878582309386074678 747790483 1 0.0 1917.0\n", - "5 5165654450418431354 1099315293 1 0.0 1638.0\n", - "6 8645800994482743477 1485498797 1 0.0 1368.0\n", - "7 7737622759347273505 1321981575 1 0.0 1638.0\n", - "8 5088707321165044480 1666586595 1 0.0 1087.0\n", - "9 5103785222818805543 1448320704 1 0.0 1828.0\n", + "0 6443990727843722078 -548015798 1 0.0 475.0\n", + "1 6826459065693194880 -548015798 1 0.0 475.0\n", + "2 7179214573492799430 1256412809 1 0.0 508.0\n", + "3 8292306315184671378 915247667 1 0.0 582.0\n", + "4 8554540233682654041 1742835715 1 0.0 1087.0\n", + "5 5823434249592995535 -36496520 1 0.0 1638.0\n", + "6 7874580368516745438 614013419 1 1.0 1917.0\n", + "7 6330773858554857995 614013419 1 0.0 1917.0\n", + "8 8083555554150073013 -1698684098 1 0.0 1638.0\n", + "9 4932438904351546868 1270475456 1 0.0 1471.0\n", + "chDB time: 0.26853251457214355\n", "chDB return:\n", " 7045311802744285412,-1341502114,1,0,1996\n", "7997911216135529594,-1050444826,1,0,1750\n", @@ -1177,6 +1208,7 @@ "4848806411334622685,2132338069,1,0,1638\n", "\n", "Q33: SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.22488951683044434\n", "DuckDB return:\n", " URL c\n", "0 http://sp-money.yandex.ru/comme%2F27.0.1453.11... 100821\n", @@ -1189,6 +1221,7 @@ "7 http://afisha.yandex.ru/region-ware-ne-niz%2F%... 26520\n", "8 http://sib1.adriver 25242\n", "9 http://sp-money.yandex.ua/search&event=little 17068\n", + "chDB time: 0.2865910530090332\n", "chDB return:\n", " \"http://sp-money.yandex.ru/comme%2F27.0.1453.116 Safari\",100821\n", "\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",90604\n", @@ -1202,6 +1235,7 @@ "\"http://sp-money.yandex.ua/search&event=little\",17068\n", "\n", "Q34: SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.22495079040527344\n", "DuckDB return:\n", " 1 URL c\n", "0 1 http://sp-money.yandex.ru/comme%2F27.0.1453.11... 100821\n", @@ -1214,6 +1248,7 @@ "7 1 http://afisha.yandex.ru/region-ware-ne-niz%2F%... 26520\n", "8 1 http://sib1.adriver 25242\n", "9 1 http://sp-money.yandex.ua/search&event=little 17068\n", + "chDB time: 0.18627619743347168\n", "chDB return:\n", " 1,\"http://sp-money.yandex.ru/comme%2F27.0.1453.116 Safari\",100821\n", "1,\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",90604\n", @@ -1227,6 +1262,7 @@ "1,\"http://sp-money.yandex.ua/search&event=little\",17068\n", "\n", "Q35: SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;\n", + "DuckDB time: 0.10100579261779785\n", "DuckDB return:\n", " ClientIP (ClientIP - 1) (ClientIP - 2) (ClientIP - 3) c\n", "0 -1698104457 -1698104458 -1698104459 -1698104460 29119\n", @@ -1239,6 +1275,7 @@ "7 -1313501018 -1313501019 -1313501020 -1313501021 2746\n", "8 1151807695 1151807694 1151807693 1151807692 2702\n", "9 -267589304 -267589305 -267589306 -267589307 2526\n", + "chDB time: 0.11476325988769531\n", "chDB return:\n", " -1698104457,-1698104458,-1698104459,-1698104460,29119\n", "-1175819552,-1175819553,-1175819554,-1175819555,16854\n", @@ -1252,6 +1289,7 @@ "-267589304,-267589305,-267589306,-267589307,2526\n", "\n", "Q36: SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;\n", + "DuckDB time: 0.13180303573608398\n", "DuckDB return:\n", " URL PageViews\n", "0 http://irr.ru/index.php?showalbum/login-leniya... 85646\n", @@ -1264,6 +1302,7 @@ "7 http://irr.ru/index.php?showalbum/login-kupalnik 3633\n", "8 http://irr.ru/index.php?showalbum/login-kapust... 3363\n", "9 http://komme%2F27.0.1453.116 Safari 2538\n", + "chDB time: 0.15227031707763672\n", "chDB return:\n", " \"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",85646\n", "\"http://komme%2F27.0.1453.116\",42422\n", @@ -1277,6 +1316,7 @@ "\"http://komme%2F27.0.1453.116 Safari\",2538\n", "\n", "Q37: SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;\n", + "DuckDB time: 0.1774451732635498\n", "DuckDB return:\n", " Title PageViews\n", "0 Тест (Россия) - Яндекс 102228\n", @@ -1289,6 +1329,7 @@ "7 AUTO.ria.ua ™ - Аппер 11611\n", "8 OWAProfessign), продать 8965\n", "9 Труси - Шоубиз 8445\n", + "chDB time: 0.16326427459716797\n", "chDB return:\n", " \"Тест (Россия) - Яндекс\",102228\n", "\"Шарарай), Выбрать! - обсуждаются на голд: Шоубиз - Свободная историс\",68968\n", @@ -1302,112 +1343,121 @@ "\"Труси - Шоубиз\",8445\n", "\n", "Q38: SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\n", + "DuckDB time: 0.1447598934173584\n", "DuckDB return:\n", " URL PageViews\n", - "0 http://video.yandex.ru/image 2\n", - "1 http://kommedostan-rentPeriod=2&marka=0&top=0&... 2\n", - "2 http://afisha.yandex.ru/real-esta.info/news.ru... 2\n", - "3 http://kinopoisk.ru/Web 2\n", - "4 http://stalker-pub-20087898675494,960948/#page... 2\n", - "5 http://loveplanet.ru/film/4551685&pt=b&pd=9&pw... 2\n", - "6 http://stalker-pub-20087898675494,960948/#page... 2\n", - "7 http://kinopoisk.ru/exp?sid=373888 Version%2F1... 2\n", - "8 http://omsk/evential/housession%3D90%26rnd%3D8... 2\n", - "9 http://omsk/evential/housession%3D90%26rnd%3D8... 2\n", + "0 http://belgorodaetsya-na-briuki-penopoisk.ru/G... 2\n", + "1 http://afisha.mail.ru/search/commu_2-gorod55 2\n", + "2 http://auto.ria.ua/auto_gazine.ru/search 2\n", + "3 http://mysw.info/forum.rostova 2\n", + "4 http://loveplanet.ru/jobinmoscow-Kriliattribu&... 2\n", + "5 http://pogoda.yandex.ru/image 2\n", + "6 http://guid=6&pw=2&pv=0&price=690&s_yers=1916 2\n", + "7 http://stalker-pub-20087898675494,960948/#page... 2\n", + "8 http://stalker-pub-20087898675494,960948/#page... 2\n", + "9 http://kaluga/?ext=фильм огурцы размеры - Для 2\n", + "chDB time: 0.16821551322937012\n", "chDB return:\n", - " \"http://ria.ua/zakuskaet-ru/#!/search.php?f=1560272,972590\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D%26CompPath%3D278885%26bid%3D0%26u_h%3D728%26fh_page=1080&with_exchangeTypeId=0&engineVolumeTo=&powerTo=&fuelRatesType=lists=2007950713/8586\",2\n", - "\"http://omsk.spb.ru/filmId=RUb3Hf2m0Cw&where=all&text\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D%26xpid%3D0%26ref%3D%2F%2Fwwww.bonprix.ru/cgi-bin/click.cgi%3Fsid%3D1216/0000461323935366106621&pr=2100911434&clid=True&uA=Mozilla%2F&sr=http://afisha.mail.asp?firms\",2\n", - "\"http://forum/topnews/222936206752816-170¤cy\",2\n", - "\"http://masterlitama-lab.com/commercial/secondary/Micubicfun/crystavropol/o\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D//ad.adriver.ru/photo=0&is_hot=0&auto_id=577&oki=1&op_prodam-1-komn-kvarti-m.ru/allprice_do=¤cy=1#countpage_type=city=0&page=1024&wi=1280&lo=http://diary.su\",2\n", - "\"http://pogoda.yandex.ru/real\",2\n", - "\"http://myloveplanet.ru/games\",2\n", - "\"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D//ad.adriver.ru/photo=0&is_hot=0&auto_id=577&oki=1&op_prodam-1-komn-kvarti-m.ru/allprice/1439/EPS/\",2\n", + " \"http://stalker-pub-20087898675494,960948/#page_type%3D0%26pz%3D0%26rleurl%3D%26CompPath%3D278885%26bid%3D0%26u_h%3D728%26fh_page=1080&with_exchangeTypeId=0&engineVolumeFrom=&power_name=Блуза&op_product&op_category\",2\n", + "\"http://stalker-pub-20087898675494,960948/#page_type%3D260117152337&spn=1395,9455989.ya.ru/workman/refrigeratorage/hug/d-gofrirodam-tonkolom/Drop cs2a&firm=1&marka=0&marka=9&model=0&scroll_to_auto_id=100&curre-bolieries.ru/main.aspx?group=jett_anapazolusapozhany\",2\n", + "\"http://forum/FORUM_ID=56887958/detail.aspx?sort_key=58&op_product\",2\n", + "\"http://sravni.ru/search=0&city_id\",2\n", + "\"http://video.yandex.ru/luboj-92687295\",2\n", + "\"http://forum/topnews/2229737/conteneginal.aspx?page\",2\n", + "\"http://sslow_13507.html?aspx?naId=649&stavkaz.com/iframe-owa.html?1=1&cid=1&marketingsteklo.ru/r/lyrsense\",2\n", + "\"http:%2F%2Ftregister_pf[CML2_BIOCERA\",2\n", + "\"http://bdsmpeople.ru/film/64544.6900205595\",2\n", + "\"http://alpari.yandex.ru/saint-peters\",2\n", "\n", "Q39: SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;\n", + "DuckDB time: 0.2037675380706787\n", "DuckDB return:\n", " TraficSourceID SearchEngineID AdvEngineID \\\n", "0 -1 0 0 \n", - "1 -1 0 0 \n", - "2 -1 0 0 \n", + "1 5 0 0 \n", + "2 5 0 0 \n", "3 -1 0 0 \n", - "4 0 0 0 \n", - "5 -1 0 0 \n", + "4 -1 0 0 \n", + "5 0 0 0 \n", "6 -1 0 0 \n", - "7 0 0 0 \n", - "8 0 0 0 \n", + "7 -1 0 0 \n", + "8 -1 0 0 \n", "9 -1 0 0 \n", "\n", " Src \\\n", - "0 http://state=19945206/foto-4/login-2491724/?bu... \n", - "1 http://state=19945206/foto-4/login-kategoriya/... \n", - "2 http://state=19945206/foto-4/login-ssva/460357... \n", - "3 http://state=19945206/foto-4/login-2491724/?bu... \n", - "4 \n", - "5 http://state=19945206/foto-4/login-2491724/?bu... \n", - "6 http://kinopoisk.ru/?state \n", - "7 \n", - "8 \n", - "9 http://state=19945206/foto-4/login-2006/makumi... \n", + "0 http://go.mail.ru/yandsearch?lr \n", + "1 http://state=199450984062 \n", + "2 http://go.mail.ru/yandsearch?lr \n", + "3 http://state=19945206/foto-4/login-2006/makumi... \n", + "4 http://state=19945206/foto-4/login-2006/makumi... \n", + "5 \n", + "6 http://state=19945206/foto-4/login-2006/makumy... \n", + "7 http://state=19945206/foto-4/login-2006/makumi... \n", + "8 http://state=19945206/foto-4/login-2491724/?bu... \n", + "9 http://state=19945206/foto-4/login-2491724/?bu... \n", "\n", " Dst PageViews \n", - "0 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", - "1 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", - "2 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", - "3 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", - "4 http://irr.ru/index.php?showalbum/login-elie-b... 13 \n", + "0 http://komme%2F27.0.1453.116 13 \n", + "1 http:%2F%2Fwwwwww.bonprix.ru/myAccountry 13 \n", + "2 http://afisha.yandex.ru 13 \n", + "3 http://irr.ru/index.php?showalbum/logabass.ru/... 13 \n", + "4 http://irr.ru/index.php?showalbum/login 13 \n", "5 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", - "6 http://irr.ru/index.php?showalbum/login-rent/o... 13 \n", - "7 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "6 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "7 http://irr.ru/index.php?showalbum/login-leniya... 13 \n", "8 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", - "9 http://irr.ru/index.php?showalbum/login-leniya... 13 \n", + "9 http://irr.ru/index.php?showalbum/login-kapust... 13 \n", + "chDB time: 0.22154474258422852\n", "chDB return:\n", - " -1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/games=6500&url=www.svoboda.yandex.ru/p3200\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", - "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert26612&street=994090808%2F&sr=http://news/post\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2415040,5;4497.html%3Fhtml_params%3Drhost\",13\n", - "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert267695,938663335030.html%3Fhtml_params%3Drhost\",13\n", - "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-elie-bielie-erotichamber=745-A6AC-46256&model=3159&input\",13\n", - "0,0,0,\"\",\"http://irr.ru/index.php?showalbum/login-mansk/men.aspx?group_cod_1s=8576/#/shop.ru/moscow/choosO6\",13\n", - "1,0,0,\"http://forums/liiiervierk-suppohudeemvmesting/294465&op_categoriya\",\"http://komme%2F27.0.1453.116\",13\n", + " -1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/a-myprofile%3Dgetnew=&type=simage\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/adv?id=299953&lr=39&text=пневмоскве\",\"http://irr.ru/index.php?showalbum/login\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert2677587.12500&matcheskiy-r_n/tiid=0&last_auto\",13\n", + "5,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.rambler.html?albumfoto-15.xhtml?city\",\"http://love.ru/a-myprofi\",13\n", "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumiroshoowbiz/down%2Fholodilnik.ru/76/~8/\",\"http://irr.ru/index.php\",13\n", "1,0,0,\"http://google.ru/forum\",\"http://irr.ru/index.php?showalbum/login\",13\n", "-1,0,0,\"http://kinopoisk.ru/yandex.ru/index.ru/?a\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", + "5,0,0,\"http://state=199450984062\",\"http:%2F%2Fwwwwww.bonprix.ru/myAccountry\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2006/makumirostova.ru/GameMain.aspx?sort=RublePrice=от\",\"http://irr.ru/index.php?showalbum/login-leniya7777294,938303130\",13\n", + "-1,0,0,\"http://state=19945206/foto-4/login-2491724/?bundlers/search?text\",\"http://irr.ru/index.php?showalbum/login-kapusta-advert26092/make=KIA/page/1762058;40;42&pv=16&ll\",13\n", "\n", "Q40: SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;\n", + "DuckDB time: 0.060501813888549805\n", "DuckDB return:\n", " URLHash EventDate PageViews\n", "0 7516345568886640333 2013-07-15 23\n", - "1 -1285046671250476833 2013-07-15 23\n", - "2 -8435826299601811261 2013-07-15 23\n", - "3 7719727592795372103 2013-07-15 22\n", - "4 -3172049944036544851 2013-07-15 22\n", - "5 -3950137591013798111 2013-07-15 22\n", - "6 1387759335351574242 2013-07-15 22\n", - "7 2680587802399303961 2013-07-15 22\n", - "8 3756346524397046411 2013-07-15 22\n", - "9 3936351847986462322 2013-07-15 21\n", + "1 -8435826299601811261 2013-07-15 23\n", + "2 -1285046671250476833 2013-07-15 23\n", + "3 3756346524397046411 2013-07-15 22\n", + "4 7719727592795372103 2013-07-15 22\n", + "5 1387759335351574242 2013-07-15 22\n", + "6 2680587802399303961 2013-07-15 22\n", + "7 -3950137591013798111 2013-07-15 22\n", + "8 -3172049944036544851 2013-07-15 22\n", + "9 -6314751298222231545 2013-07-15 21\n", + "chDB time: 0.09494566917419434\n", "chDB return:\n", - " 7516345568886640333,\"2013-07-15 08:00:00.000000000\",23\n", - "-8435826299601811261,\"2013-07-15 08:00:00.000000000\",23\n", - "-1285046671250476833,\"2013-07-15 08:00:00.000000000\",23\n", + " -1285046671250476833,\"2013-07-15 08:00:00.000000000\",23\n", + "8436286387721556030,\"2013-07-15 08:00:00.000000000\",23\n", + "7516345568886640333,\"2013-07-15 08:00:00.000000000\",23\n", "2680587802399303961,\"2013-07-15 08:00:00.000000000\",22\n", "1387759335351574242,\"2013-07-15 08:00:00.000000000\",22\n", - "-3172049944036544851,\"2013-07-15 08:00:00.000000000\",22\n", "7719727592795372103,\"2013-07-15 08:00:00.000000000\",22\n", "-3950137591013798111,\"2013-07-15 08:00:00.000000000\",22\n", + "-3172049944036544851,\"2013-07-15 08:00:00.000000000\",22\n", "3756346524397046411,\"2013-07-15 08:00:00.000000000\",22\n", - "5594816550667140150,\"2013-07-15 08:00:00.000000000\",21\n", + "-4585239266146446633,\"2013-07-15 08:00:00.000000000\",21\n", "\n", "Q41: SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;\n", + "DuckDB time: 0.06289076805114746\n", "DuckDB return:\n", " Empty DataFrame\n", "Columns: [WindowClientWidth, WindowClientHeight, PageViews]\n", "Index: []\n", + "chDB time: 0.10314488410949707\n", "chDB return:\n", " \n", "Q42: SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;\n", + "DuckDB time: 0.05712485313415527\n", "DuckDB return:\n", " M PageViews\n", "0 2013-07-15 12:40:00 434\n", @@ -1420,19 +1470,30 @@ "7 2013-07-15 12:47:00 381\n", "8 2013-07-15 12:48:00 385\n", "9 2013-07-15 12:49:00 415\n", + "chDB time: 0.07111358642578125\n", "chDB return:\n", " \n" ] }, { "data": { - "image/png": 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jhx56yKjIAAAALsGUWQCAu7FfCwAwCo3mAAAAAAAAOE1qaqrREQBJUmhoaJ/qmpubXZwEwLns2bNHixcv1rBhwzRlyhSZzWa9//77SklJUUFBgdatW6c777xTc+bMkb+/v0pKSvTUU09p6dKlmjhxosaPH2/0VwAAAOgzpswCANyN/VoAgFFoNAcAAAAAABgEmJ6GwaqhoUEmk6nbFOSeMplMbkgE4EzWrFkjSdq8ebNmzJghSXrvvfd022236ac//alSUlK0cePGrvVWq1Xh4eGaPXu21q5dq3Xr1hmSGwAAwBWYMgsAAABgsKLRHAAAAAAAYBDo6fS0yspKbdmyRTU1NWpsbNTRo0clSSNHjlRwcLAsFotmzpypyMhIT0UHzsnf31+HDh1SbW2tRo0a1aMap9OpGTNmqLKy0s3pAHxrz549slgsXU3mkjR16lRNmDBBNptNy5cvP63mvvvuU0ZGhnbv3u3JqAAAAC7HlFkAQF+xXwsA6O9oNAcAAAAAABgEvm96WkNDg+bPn69du3ZJ0hmnQ9tsNhUVFWnlypWyWq0qKChQSEiIuyIDPRIdHa3i4mLZ7XaFh4f3uM5sNrsxFYBTHTx4UBMnTjztelhYmGw2m6655poz1l133XUqKSlxczoAAAAAAPoX9msBAAMFjeYAAAAAAACDwLmmpzU3Nys2Nlatra2yWCyaNWuWoqKiFBgYKB8fH0lSR0eH7Ha7KioqVFhYqJ07dyouLk42m00BAQGe+hrAaaKjo7Vt2zaVl5dr2rRpRscBcBa+vr766quvTrvu7e0tSRoxYsQZ6y6++GKdPHnSrdkAAAD6iimzAAadx/3ccM92199zkGO/FgAwkNBoDgAAAAAAMMhlZWWptbVVeXl5WrJkyVnXWSwWJScnKzMzU3l5eVq2bJmys7O1YcMGz4UFTmG1WhUREaH29t49tFy4cKGSkpLclArAqa644grZ7fbTrk+aNEkXXnj2RxEtLS267LLL3BkNAACg15gyC6C/aWtr0549ezR8+HDFxsbqBz/4Qdd7mzdv1ptvvqkvvvhCYWFhmjt3rm666SYD0+L7sF8LABhIaDQHAAAAAADox1wxPW379u2KiYk550OLUy1dulSFhYUqLi4+368AnJeEhARVVlb2um7BggVuSAPgbCIiIlRUVKSOjo6u6WuSNG/ePM2bN++MNd98841sNpsmTJjgoZQAAADfjymzAPqbdevW6ZFHHuk6ReqSSy7Rxo0bNW3aNC1atEjr16/v9oOYtWvXas2aNXrooYeMiozvwX4tAGAgodEcAAAAAACgH3Ll9LS2tjYlJCT0OkNwcLCqqqp6XQcAGHqSkpJUV1en2tpa3XzzzT2qeeONN9Te3i6r1erecAAAAL3AlFkA/cmePXu0ePFiDRs2TFOmTJHZbNb777+vlJQUFRQUaN26dbrzzjs1Z84c+fv7q6SkRE899ZSWLl2qiRMnavz48UZ/BZwB+7UAgIGERnMAAAAAAAYBjk4dXFw9PS0oKEilpaVyOBwaMWJEjzI4HA6VlpZqzJgxLv9+AIDBZ+7cuZo7d26vam688Ubt3LlT119/vZtSAQAA9B5TZgH0J2vWrJH0zz3eGTNmSJLee+893XbbbfrpT3+qlJQUbdy4sWu91WpVeHi4Zs+erbVr12rdunWG5Ma5sV8LABhIhhkdAAAAAAAAnJ9169ZpzJgxuuuuuzR9+nSFhYXpr3/9qyRp0aJFmjVrll5++WUVFxfrueeeU0xMjJ599lmDU+Ncvjs9raqqSpmZmUpOTpbFYlFYWJjCwsK6TU6rrq7W008/rc8//1zZ2dmn3S8lJUXNzc1KTExUTU3N935+TU2NEhMT1dLSotmzZ7vjKwIAoPDwcE2aNEn+/v5GRwEAAOjS1tZ2xtPCvk9wcLDa2tpcHwjAkLZnzx5ZLJauJnNJmjp1qiZMmKC2tjYtX778tJr77rtPISEh2r17tyejohfYrwUADCRMNAcAAAAAYADj6NTBydXT0zIyMrRjxw6VlZUpMjJSYWFhXRPSv52Y43A4uiak19fXy+l0KjY2Vunp6a76WoDHrFixQgcOHJDJZFJBQYHRcQAAAAAMIEyZBdCfHDx4UBMnTjztelhYmGw2m6655poz1l133XUqKSlxczr0Ffu1AICBhEZzAAAAAAAGMI5OHZza2tqUkJDQ67rg4GBVVVWddt3b21slJSVatWqV8vPzVVdXp7q6OkmSyWSSJDmdzq71fn5+SktLU2Zmpry8vPr2JQADFRUVad++fTSaAwNAVVWVjhw50qf/7gEAALhDSkqKcnNzlZiYqPz8fFkslnOur6mpUWpqqlpaWpSVleWhlACGCl9fX3311VenXff29paks/4g5uKLL9bJkyfdmg19x34tAGAgodEcAAAAAIAB7FxHp9pstrMenZqRkcHRqf2YO6aneXl5KTc3Vzk5OSorK1N1dbWampp07NgxSf98aBUUFKSIiAjFx8fLbDa77PsAnpaWlqaDBw8aHQNADyxevFjl5eXq7Ow0OgoAAIAkpswC6F+uuOIK2e32065PmjRJF1549ravlpYWXXbZZe6MhvPEfi0AYKCg0RwAAAAAgAGMo1MHJ3dOTzObzbJarbJarS5MDPQvqampRkcA0AvfndIGAABgNKbMAuhPIiIiVFRUpI6ODvn4+HRdnzdvnubNm3fGmm+++UY2m00TJkzwUEqcD/ZrAQD9HY3mAAAAAAAMYBydOjgxPQ0AAAAAAOMwZRZAf5GUlKS6ujrV1tbq5ptv7lHNG2+8ofb2dhqXAQCAS9BoDgAAAADAAMbRqYMT09OAM6usrNSWLVtUU1OjxsZGHT16VJI0cuRIBQcHy2KxaObMmYqMjDQ4KTD0hIaG9qmuubnZxUkAAABchymzAIw2d+5czZ07t1c1N954o3bu3Knrr7/eTakAAMBQQqM5AAAAAAADGEenDl5MTwP+T0NDg+bPn69du3ZJ6v5Di2/ZbDYVFRVp5cqVslqtKigoUEhIiIeTAkNXQ0ODTCbTGf/5/D7f/ogKAAAAAHD+wsPDFR4ebnQMAAAwSNBoDgAAAADAAMbRqYMf09Mw1DU3Nys2Nlatra2yWCyaNWuWoqKiFBgY2PUDm46ODtntdlVUVKiwsFA7d+5UXFycbDabAgICDP4GwNDg7++vQ4cOqba2VqNGjepRjdPp1IwZM1RZWenmdBiM2tratGfPHg0fPlyxsbH6wQ9+0PXe5s2b9eabb+qLL75QWFiY5s6dq5tuusnAtAAAAAAAAMDARKM5AAAAAAADGEenAhjssrKy1Nraqry8PC1ZsuSs6ywWi5KTk5WZmam8vDwtW7ZM2dnZ2rBhg+fCAkNYdHS0iouLZbfbezU5jxM50Bfr1q3TI488oq+++kqSdMkll2jjxo2aNm2aFi1apPXr13ebrr927VqtWbNGDz30kFGRAQAAAI+qqqrSkSNHlJCQYHQUAAAwwA0zOgAAAAAAAPCs8PBwTZo0Sf7+/kZHAYDvtX37dsXExJyzyfxUS5cuVUxMjIqLi90XDEA30dHRcjqdKi8vNzoKBrk9e/Zo8eLFOn78uKZMmaLExEQdPXpUKSkpeuONN7Ru3TrNnDlTr7/+ut5//31lZ2fLy8tLS5cuVVVVldHxAQAAAI9YvHixpkyZYnQMAAAwCDDRHAAAAAAAAEC/1dbW1qfpW8HBwTQUAh5ktVoVERGh9vb2XtUtXLhQSUlJbkqFwWjNmjWSpM2bN2vGjBmSpPfee0+33XabfvrTnyolJUUbN27sWm+1WhUeHq7Zs2dr7dq1WrdunSG5AQAAAE/77ik/AAAAfUWjOQAAAAAAQxBHpwIYKIKCglRaWiqHw6ERI0b0qMbhcKi0tFRjxoxxczoA30pISFBlZWWv6xYsWOCGNBjM9uzZI4vF0tVkLklTp07VhAkTZLPZtHz58tNq7rvvPmVkZGj37t2ejAoAAAAAAAAMeDSaAwAAAAAwBC1evFjl5eXq7Ow0OgoAnFNKSopyc3OVmJio/Px8WSyWc66vqalRamqqWlpalJWV5aGUAABPOXjwoCZOnHja9bCwMNlsNl1zzTVnrLvuuutUUlLi5nQAAACAa4WGhvaprrm52cVJAADAUEWjOQAAAAAAQxRHpwIYCDIyMrRjxw6VlZUpMjJSYWFhioqKUmBgYNeEc4fDIbvdroqKCtXX18vpdCo2Nlbp6ekGpwf6t7a2Nu3Zs0fDhw9XbGysfvCDH3S9t3nzZr355pv64osvFBYWprlz5+qmm24yMC3wT76+vvrqq69Ou+7t7S1JZz394uKLL9bJkyfdmg0AAABwtYaGBplMpj7t5ZpMJjckAgAAQw2N5gAAAB7y6aefqrm5WaNHj1ZwcPA513700UdqaWlRQkKCh9IBAAAA/ZO3t7dKSkq0atUq5efnq66uTnV1dZL+74Hpdx+2+vn5KS0tTZmZmfLy8jIkMzAQrFu3To888khXw+4ll1yijRs3atq0aVq0aJHWr1/f7Z+ttWvXas2aNXrooYeMigxIkq644grZ7fbTrk+aNEkXXnj2x14tLS267LLL3BkNAAAAcDl/f38dOnRItbW1GjVqVI9qnE6nZsyYocrKSjenAwAAQwGN5gAAAG728ccf6/7779d//Md/dF2zWCxavXq1br/99jPW/OpXv9LLL7+sEydOeComAGCA4uhUfK/H/dxwz3bX3xM4By8vL+Xm5ionJ0dlZWWqrq5WU1OTjh07Jumf022DgoIUERGh+Ph4mc1mgxMD/duePXu0ePFiDRs2TFOmTJHZbNb777+vlJQUFRQUaN26dbrzzjs1Z84c+fv7q6SkRE899ZSWLl2qiRMnavz48S7JsWLFCh04cEAmk0kFBQUuuScGv4iICBUVFamjo0M+Pj5d1+fNm6d58+adseabb76RzWbThAkTPJQSAAAAcI3o6GgVFxfLbrcrPDy8x3XsjfRfIY9tdfk9G7xdfksAALrQaA4AAOBGBw8e1KRJk9TS0iJJuuyyy3T48GFVV1dr+vTpeuSRR/T0008bnBIAMJBxdCqAocRsNstqtcpqtRodBRjQ1qxZI0navHmzZsyYIUl67733dNttt+mnP/2pUlJStHHjxq71VqtV4eHhmj17ttauXat169a5JEdRUZH27dtHozl6JSkpSXV1daqtrdXNN9/co5o33nhD7e3t/PcDAAAAA050dLS2bdum8vJyTZs2zeg4AABgCKLRHAAAwI1Wr16tlpYWJSUlqaCgQFdeeaXa29v13HPP6YknntCaNWv02Wef6ZVXXjnn8c4AAJwNR6cCAIDe2rNnjywWS1eTuSRNnTpVEyZMkM1m0/Lly0+rue+++5SRkaHdu3e7LEdaWpoOHjzosvthaJg7d67mzp3bq5obb7xRO3fu1PXXX++mVACAwcItU2afvMPl9wQwdFitVkVERKi9vXcnDC5cuFBJSUluSgUAAIYSupkAAADcaOvWrbrsssv02muvaeTIkZIkPz8/rVixQsnJybr33nv1+uuvq729XZs2bdJFF11kcGIAwEDD0akAAKC3Dh48qIkTJ552PSwsTDabTddcc80Z66677jqVlJS4LEdqaqrL7gWcS3h4eK/+tzIAAADQXyQkJPRpYMiCBQvckAYAAAxFNJoDAAC4UUNDg26//fauJvPvioyM1N/+9jdNnz5d27dvV2JiorZu3XrGtQAAnA1Hpw4+rp6e1uDt0tsBAAYBX19fffXVV6dd9/b+5380RowYcca6iy++WCdPnnRrNgAAAAAAAABA/0GjOQAAgBuZTKZzToy9/PLLtWvXLs2cOVO7du3S5MmT9c4773gwIQBgoOPoVAAA0FtXXHGF7Hb7adcnTZqkCy88+2ODlpYWXXbZZd97/8rKSm3ZskU1NTVqbGzU0aNHJUkjR45UcHCwLBaLZs6cqcjIyL5/CaCXqqqqdOTIESUkJBgdBQAAAAAAABgwaDQHAABwo9DQUFVUVJxzja+vr7Zv364f/ehH2rJlixISEhQYGOihhACAgY6jUwEAQG9FRESoqKhIHR0d8vHx6bo+b948zZs374w133zzjWw2myZMmHDW+zY0NGj+/PnatWuXJMnpdJ62xmazqaioSCtXrpTValVBQYFCQkLO6/sAPbF48WKVl5ers7PT6CgAAAAAAADAgEGjOQAAgBtNmjRJzz//vGw2m2666aazrvPy8lJRUZHmzZunP/3pT/rwww89mBIAAAAAMJQkJSWprq5OtbW1uvnmm3tU88Ybb6i9vV1Wq/WM7zc3Nys2Nlatra2yWCyaNWuWoqKiFBgY2NXM3tHRIbvdroqKChUWFmrnzp2Ki4uTzWZTQECAq74ecFZn+vEDAAAAMNisWLFCBw4ckMlkUkFBgdFxAADAAEejOQAAgBvdddddWrt2rZ5++mlt3LjxnGsvuOACvfLKK7rkkkv07LPPymQyeSglAAAAAGAomTt3rubOndurmhtvvFE7d+7U9ddff8b3s7Ky1Nraqry8PC1ZsuSs97FYLEpOTlZmZqby8vK0bNkyZWdna8OGDb3KAwAAAAA4s6KiIu3bt49GcwAA4BI0mgMAALjR5MmTtWPHDg0bNqzHNc8884ymTp2qw4cPuzEZAAAAAAA9Fx4ervDw8LO+v337dsXExJyzyfxUS5cuVWFhoYqLi12QEENFaGhon+qam5tdnAQAAADon9LS0nTw4EGjYwAAgEGCRnMAAAA3uvDCCzV16tRe1915551uSAMAwD9xdCoAAHC1trY2JSQk9LouODhYVVVVrg+EQauhoUEmk0lOp7PXtZweBwAAgKEgNTXV6AgAAGAQodEcAAAAAIAhhqNTAQBAX1RVVenIkSNnbCgPCgpSaWmpHA6HRowY0aP7ORwOlZaWasyYMa6OikHM399fhw4dUm1trUaNGtWjGqfTqRkzZqiystLN6QAAAAAAAIDBhUZzAACAfuhcD+8BADhfHJ0KYMB43M8N92x3/T2BIWLx4sUqLy9XZ2fnae+lpKQoNzdXiYmJys/Pl8ViOee9ampqlJqaqpaWFmVlZbkrMgah6OhoFRcXy263Kzw8vMd1ZrPZjakAAOiZTz/9VM3NzRo9erSCg4PPufajjz5SS0sLzwkAdKmsrNSWLVtUU1OjxsZGHT16VJI0cuRIBQcHy2KxaObMmYqMjDQ4KQAAGExoNAcAAOiHzvXwHgCA88XRqQAAoK+cTucZr2dkZGjHjh0qKytTZGSkwsLCFBUVpcDAwK4J5w6HQ3a7XRUVFaqvr5fT6VRsbKzS09M9+RUwwEVHR2vbtm0qLy/XtGnTjI4DAECPfPzxx7r//vv1H//xH13XLBaLVq9erdtvv/2MNb/61a/08ssv68SJE56KCaCfamho0Pz587Vr1y5JZ/5zmc1mU1FRkVauXCmr1aqCggKFhIR4OCkAABiMaDQHAADop8728B4AAAAAgP7G29tbJSUlWrVqlfLz81VXV6e6ujpJkslkktT9z7l+fn5KS0tTZmamvLy8DMmMgclqtSoiIkLt7b07oWLhwoVKSkpyUyoAAM7u4MGDmjRpklpaWiRJl112mQ4fPqzq6mpNnz5djzzyiJ5++mmDUwLor5qbmxUbG6vW1lZZLBbNmjWr60e9Pj4+kqSOjo6uH/UWFhZq586diouLk81mU0BAgMHfAAAADHQ0mgMAAAAAMEhwdCoAAOiJ0NDQPtU1Nzef830vLy/l5uYqJydHZWVlqq6uVlNTk44dOyZJ8vX1VVBQkCIiIhQfHy+z2dynHBjaEhISVFlZ2eu6BQsWuCENAADfb/Xq1WppaVFSUpIKCgp05ZVXqr29Xc8995yeeOIJrVmzRp999pleeeUVXXghLRwAusvKylJra6vy8vK0ZMmSs66zWCxKTk5WZmam8vLytGzZMmVnZ2vDhg2eCwsAAAYl/pQCAADgRu56eA8AwHdxdCoAAOiNhoYGmUymPp2k9e108nMxm82yWq2yWq19SAcAADC4bN26VZdddplee+01jRw5UtI/T3dZsWKFkpOTde+99+r1119Xe3u7Nm3apIsuusjgxAD6k+3btysmJuacTeanWrp0qQoLC1VcXOy+YAAAYMig0RwAAMCN3P3wHgAAjk4FAAC95e/vr0OHDqm2tlajRo3qUY3T6dSMGTP6NEkaAABgKGtoaNDtt9/e1WT+XZGRkfrb3/6m6dOna/v27UpMTNTWrVvPuBbA0NTW1qaEhIRe1wUHB6uqqsr1gQAAwJBDozkAAIAb8fAeAOBuHJ0KAAB6Kzo6WsXFxbLb7QoPD+9xndlsdmMqAACAwclkMp3zf0ddfvnl2rVrl2bOnKldu3Zp8uTJeueddzyYEEB/FhQUpNLSUjkcDo0YMaJHNQ6HQ6WlpRozZoyb0wEAgKFgmNEBAAAABrPo6GhJkt1u1xVXXNGjv0aPHs3DewBAj/X16NSYmBiOTgUAYIiKjo6W0+lUeXm50VEAj1ixYoXmz5+vBQsWGB0FADAEhYaGqqKi4pxrfH19tX37ds2cOVMVFRVKSEhQc3OzhxIC6M9SUlLU3NysxMRE1dTUfO/6mpoaJSYmqqWlRbNnz/ZAQgAAMNgx0RwAAMCNoqOjtW3bNpWXl2vatGlGxwEADEIcnQoAAHrLarUqIiJC7e3tvapbuHChkpKS3JQKcJ+ioiLt27dPJpNJBQUFRscBAAwxkyZN0vPPPy+bzaabbrrprOu8vLxUVFSkefPm6U9/+pM+/PBDD6YE0F9lZGRox44dKisrU2RkpMLCwhQVFaXAwMCuCecOh0N2u10VFRWqr6+X0+lUbGys0tPTDU4PAAAGAxrNAQAA3IiH9wAAd+PoVAAA0FsJCQmqrKzsdR3ToDFQpaWl6eDBg0bHAAAMUXfddZfWrl2rp59+Whs3bjzn2gsuuECvvPKKLrnkEj377LMymUweSgmgv/L29lZJSYlWrVql/Px81dXVqa6uTpK6/h3hdDq71vv5+SktLU2ZmZny8vIyJDMAABhcaDQHAABwIx7eAwDcLSUlRbm5uUpMTFR+fr4sFss519fU1Cg1NVUtLS3KysryUEoAAADAOKmpqUZHAAAMYZMnT9aOHTs0bNiwHtc888wzmjp1qg4fPuzGZAAGCi8vL+Xm5ionJ0dlZWWqrq5WU1OTjh07Jkny9fVVUFCQIiIiFB8fL7PZbHBiAAAwmNBoDgAAAABwiU8//VTNzc0aPXq0goODz7n2o48+UktLixISEjyUbvDi6FQAAAAAAID+68ILL9TUqVN7XXfnnXe6IQ2AgcxsNstqtcpqtRodBQAADCE0mgMAAAAAzsvHH3+s+++/X//xH//Rdc1isWj16tW6/fbbz1jzq1/9Si+//LJOnDjhqZiDFkenAgAAYKiqrKzUli1bVFNTo8bGRh09elSSNHLkSAUHB8tisWjmzJmKjIw0OCkAAAAAAAAwMNFoDgAAAADos4MHD2rSpElqaWmRJF122WU6fPiwqqurNX36dD3yyCN6+umnDU45+HF0KgAAcLcVK1bowIEDMplMKigoMDoOhriGhgbNnz9fu3btktT9h5XfstlsKioq0sqVK2W1WlVQUKCQkBAPJwUAoO+qqqp05MgRTgQEAAAAYCgazQEAAPoZHt4DGEhWr16tlpYWJSUlqaCgQFdeeaXa29v13HPP6YknntCaNWv02Wef6ZVXXtGFF/JHUHfj6FQAAOAuRUVF2rdvH39WheGam5sVGxur1tZWWSwWzZo1S1FRUQoMDJSPj48kqaOjQ3a7XRUVFSosLNTOnTsVFxcnm82mgIAAg78BAAA9s3jxYpWXl6uzs9PoKADO4YUXXpDdbld2drbRUQAAANyCp/wAAAD9DA/vAQwkW7du1WWXXabXXntNI0eOlCT5+flpxYoVSk5O1r333qvXX39d7e3t2rRpky666CKDEwMAAKAv0tLSdPDgwTO/+bif6z/w8XbX3xODQlZWllpbW5WXl6clS5acdZ3FYlFycrIyMzOVl5enZcuWKTs7Wxs2bPBcWAAAztOZTu0A0L+sX79ee/fupdEcAAAMWjSaAwAA9DPnfHgPAP1MQ0ODbr/99q4m8++KjIzU3/72N02fPl3bt29XYmKitm7desa1AAAA6N9SU1ONjgBIkrZv366YmJhzNpmfaunSpSosLFRxcbH7ggEAAAAAAACDEI3mAAAA/QwP7wEMJCaTSWaz+azvX3755dq1a5dmzpypXbt2afLkyXrnnXc8mBAAAADAYNLW1qaEhIRe1wUHB6uqqsr1gQAA+B6hoaF9qmtubnZxEgDn0tTU1Ke6r7/+2sVJAAAA+hcazQEAAAAAfRYaGqqKiopzrvH19dX27dv1ox/9SFu2bFFCQoICAwM9lBAAAADnUllZqS1btqimpkaNjY06evSoJGnkyJEKDg6WxWLRzJkzFRkZaXBS4J+CgoJUWloqh8OhESNG9KjG4XCotLRUY8aMcXM6AABO19DQIJPJJKfT2etak8nkhkQAziQkJKRP/8w5nU7+WQUAAIMajeYAAAAewsN7AIPRpEmT9Pzzz8tms+mmm2466zovLy8VFRVp3rx5+tOf/qQPP/zQgykBAABwqoaGBs2fP1+7du2SpDM2PtlsNhUVFWnlypWyWq0qKChQSEiIh5MC3aWkpCg3N1eJiYnKz8+XxWI55/qamhqlpqaqpaVFWVlZHkoJAMD/8ff316FDh1RbW6tRo0b1qMbpdGrGjBmqrKx0czoApxo3blyv1jc2NjLVHAAADGo0mgMAALgZD+8BDGZ33XWX1q5dq6efflobN24859oLLrhAr7zyii655BI9++yzTHkBAAAwSHNzs2JjY9Xa2iqLxaJZs2YpKipKgYGB8vHxkSR1dHTIbreroqJChYWF2rlzp+Li4mSz2RQQEGDwN8BQlpGRoR07dqisrEyRkZEKCwvr+vv32wnnDoej6+/f+vp6OZ1OxcbGKj093eD0QN+88MILstvtys7ONjoKgD6Ijo5WcXGx7Ha7wsPDe1xnNpvdmArAqUJDQ7V//369++67vToJJy4uTnv37nVjMgAAAGPRaA4AAOBGPLwHMNhNnjxZO3bs0LBhw3pc88wzz2jq1Kk6fPiwG5MBAADgbLKystTa2qq8vDwtWbLkrOssFouSk5OVmZmpvLw8LVu2TNnZ2dqwYYPnwgKn8Pb2VklJiVatWqX8/HzV1dWprq5Okrp+zPrdH/n7+fkpLS1NmZmZ8vLyMiQzcL7Wr1+vvXv30mgODFDR0dHatm2bysvLNW3aNKPjADiL6Oho7d+/XzabrVeN5gAAAIMdjeYAAABuxMN7AIPdhRdeqKlTp/a67s4773RDGgAAAPTE9u3bFRMTc84/p55q6dKlKiwsVHFxsfuCAT3k5eWl3Nxc5eTkqKysTNXV1WpqatKxY8ckSb6+vgoKClJERITi4+OZCAsAMJTValVERITa29t7Vbdw4UIlJSW5KRWAU0VHR+vPf/6z9u7dq7vvvrvHdWc6yRgAAGAwodEcAADAjXh4DwAAAADob9ra2pSQkNDruuDgYFVVVbk+ENBHZrNZVqtVVqvV6ChAjzQ1NfWp7uuvv3ZxEgCelJCQoMrKyl7XLViwwA1pAJxNcnKyGhsbNXbs2F7VPf/88zpy5IibUkkhj2116f0avF16OwAAMATQaA4AAOBGPLwHgDOrqqrSkSNH+vTvSAAAAJyfoKAglZaWyuFwaMSIET2qcTgcKi0t5Qh5ADgPISEhMplMva5zOp19qgMAAD03btw4rVmzptd1kZGRbkgDAADQf9BoDgAA4EY8vAeAM1u8eLHKy8vV2dlpdJQBj4k2AACgt1JSUpSbm6vExETl5+fLYrGcc31NTY1SU1PV0tKirKwsD6UEgMFr3LhxvVrf2NjIVHMAAAAAAGAIGs0BAADciIf3AHB2TqfT6AgAAABDUkZGhnbs2KGysjJFRkYqLCxMUVFRCgwM7PqRtMPhkN1uV0VFherr6+V0OhUbG6v09HSD0wPAwBUaGqr9+/fr3Xff7dWQibi4OO3du9eNyQAAAAAAAM6MRnMAAAA34uE9MLi98MILstvtys7ONjoKAAAA0GPe3t4qKSnRqlWrlJ+fr7q6OtXV1UmSTCaTpO4/CvTz81NaWpoyMzPl5eVlSGYAGAyio6O1f/9+2Ww2TjMEcE4rVqzQgQMHZDKZVFBQYHQcAOdQVVWlI0eOKCEhwegoAAAAbkGjOQAAgBvx8B4Y3NavX6+9e/cO6Ubz0NDQPtU1Nze7OAkAAAB6w8vLS7m5ucrJyVFZWZmqq6vV1NSkY8eOSZJ8fX0VFBSkiIgIxcfHy2w2G5wYAAa+6Oho/fnPf9bevXt1991397iOE8GAoaeoqEj79u2j0RwYABYvXqzy8nJ1dnYaHQUAAMAtaDQHAABwMx7eAxjMGhoaZDKZ+vTQ+9sf3AAAAMA4ZrNZVqtVVqvV6CgAMOglJyersbFRY8eO7VXd888/ryNHjrgpFYD+KC0tTQcPHjQ6BoAe4kdhAABgMKPRHAAAwEN4eA/0X01NTX2q+/rrr12cZODx9/fXoUOHVFtbq1GjRvWoxul0asaMGaqsrHRzOsA9XnjhBdnt9iF9mgEAAACA3hs3bpzWrFnT67rIyEg3pAHQn6WmphodAQAAAAAk0WgOAAAAAAoJCenTdG2n0znkp3JHR0eruLhYdrtd4eHhPa7j9AYMZOvXr9fevXtpNAcAAAAAAAAGidDQ0D7VNTc3uzgJAABA/0KjOQAAAAD8r3HjxvVqfWNj45Cfah4dHa1t27apvLxc06ZNMzoOAAAAAAAA0G9VVlZqy5YtqqmpUWNjo44ePSpJGjlypIKDg2WxWDRz5kxOMgAM0NDQIJPJJKfT2evaoT6QBgAADG40mgMAAAAY8kJDQ7V//369++67GjNmTI/r4uLitHfvXjcm6/+sVqsiIiLU3t7eq7qFCxcqKSnJTamAnmlqaupT3VD/gQkAAAAAz6qqqtKRI0eUkJBgdBQAfdTQ0KD58+dr165dknTGRlabzaaioiKtXLlSVqtVBQUFCgkJ8XBSYOjy9/fXoUOHVFtbq1GjRvWoxul0asaMGaqsrHRzOgAAAOPQaA4AAABgyIuOjtb+/ftls9l61WgOKSEhoU+b6AsWLHBDGqB3QkJC+jRtyOl0MqUIAADAICGPbXXp/RqevMOl9wPcYfHixSovL1dnZ6fRUQD0QXNzs2JjY9Xa2iqLxaJZs2YpKipKgYGB8vHxkSR1dHTIbreroqJChYWF2rlzp+Li4mSz2RQQEGDwNwCGhujoaBUXF8tutys8PLzHdWaz2Y2pAAAAjEejOQAAAIAhLzo6Wn/+85+1d+9e3X333T2u68sRmgD6n3HjxvVqfWNjI1PNAQAAAHgUexDAwJWVlaXW1lbl5eVpyZIlZ11nsViUnJyszMxM5eXladmyZcrOztaGDRs8FxYYwqKjo7Vt2zaVl5dr2rRpRscBAADoN2g0BwAAADDkJScnq7GxUWPHju1V3fPPP68jR464KRUAdwsNDdX+/fv17rvv9uo0g7i4OO3du9eNyQAAAAAAwGCxfft2xcTEnLPJ/FRLly5VYWGhiouL3RcMQDdWq1URERFqb2/vVd3ChQuVlJTkplQAAADGo9EcAAAAwJA3btw4rVmzptd1kZGRbkgDwFOio6O1f/9+2Wy2XjWaAwAAAEBfhIaG9qmuubnZxUkAeFJbW5sSEhJ6XRccHKyqqirXBwJwRgkJCaqsrOx13YIFC9yQBgAAoP+g0RwAAAAA4FErVqzQgQMHZDKZVFBQYHQcDGHR0dH685//rL179+ruu+/ucR1H1gMAAADoi4aGBplMpj79mcJkMrkhEQBPCAoKUmlpqRwOh0aMGNGjGofDodLSUn4YDwAAAMBwNJoDAAAAADyqqKhI+/bto9EchktOTlZjY6PGjh3bq7rnn39eR44ccVMqAAAAAIOVv7+/Dh06pNraWo0aNapHNU6nUzNmzOjThFUA/UNKSopyc3OVmJio/Px8WSyWc66vqalRamqqWlpalJWV5aGUAAAAAHBmNJoDAAAAQB9VVVXpyJEjfTr6dihLS0vTwYMHjY4BaNy4cVqz5v9n797jqizz/f+/F24OKoomJpsUmNBy1L0MKwVJWlZ7a+yww9jYaJaZuynBdEgtFQRGZr6T1vrqMDQ9JslpYjdNJOowAnkIjMFfykmph8l3g6IRMoSkKat0xPX7o4fsSETQtdbN4fX8j3td1+37bvbmcF+f63P9307PCwkJcUIaAAAAAD3dxIkTlZOTo5qaGo0ePbrD89zd3Z2YCoCzrVy5Ujt37lRhYaFCQkIUHBysCRMmaPjw4S0dzm02m2pqalRaWqqqqirZ7XaFhoZqxYoVBqcHAAAA0NtRaA4AAAAA1+i5555TUVGRLly4YHSUbiU6OtroCAAAAL1a0EvbHXq/ai+H3g4AeqyJEycqOztbRUVFuu+++4yOA1yTixcvatu2bcrKylJ5ebmOHTumM2fOSJIGDBigwMBAmc1mzZgxQzNmzJCbm5vBiY3n5eWl/Px8rVmzRqmpqaqsrFRlZaUkyWQySfru9IJLfHx8FBMTo7i4OHl6ehqSGUDHrFq1SidOnOD0TgAA0KNRaA4AAOBELN4DPd/3F4EAAAAAAACuxGKxaPz48Tp9+nSn5i1YsEDTp093Uiqg44qLizVnzhxVVla2+U7s5MmTOnnypEpLS/XWW29p1KhRSk9P1x133GFA2q7F09NTycnJSkhIUGFhoQ4ePKjjx4/r7NmzkiRvb28FBARo/PjxCg8P5yQDoJvIzMxURUUFheYAAKBHo9AcAAAAAOAQZWVlV+1mFRUVpZCQEIOTAtfnwIED+vrrrxUREWF0FAAAAADdSEREhMrKyjo97+mnn3ZCGqBzDh8+LIvFIpvNphkzZmjmzJmaMGGChg8frv79+0uSmpqaVFNTo9LSUmVkZCgrK0tTp05VUVGRRo8ebfATdA3u7u6yWCyyWCxGRwHgADExMWpoaDA6BgAAgFNRaA4AAACg17v55puvaV5tba2Dk3RP1dXVmj9/vvbs2SOp7S7vJSUlyszMVFJSkiwWi9LS0hQUFOTipIBjPPfccyoqKtKFCxeMjgIAAAAAgEskJCTo22+/1ebNm/Xwww+3OWbgwIEaM2aMxowZo8cff1yZmZl69NFHlZiYqHfffdfFiQHA+aKjo42OAAAA4HQUmgMAAADo9aqrq2UymdoskL4ak8nkhETdR21trUJDQ1VfXy+z2dyhblZ5eXkKCwtTSUmJ/P39DX4C4Npcy/cLAAAAAAC6q7y8PEVERFyxyLwtjzzyiO6++259+OGHTkwGAACAnuDixYvatm3bVU9PnjFjhmbMmCE3NzeDEwO9B4XmAAAAAHo9X19fnTx5UocOHdLgwYM7NMdut+uBBx64piOve5L4+HjV19fLarVqyZIlVxxnNpsVGRmpuLg4Wa1WLV26VKtXr9bGjRtdFxYAAAAAAADX5OzZs/L19e30PF9fXzU1NTkhEQA4T1lZ2VULHaOiohQSEmJwUgDoGYqLizVnzhxVVla22ejn5MmTOnnypEpLS/XWW29p1KhRSk9P1x133GFAWqD3odAcAAAAQK83ceJE5eTkqKamRqNHj+7wPHd3dyem6h5yc3M1adKkdovMfyg2NlYZGRnKyclxXjCgA26++eZrmldbW+vgJAAAAADQtlWrVunEiRMymUxKS0szOg56sZEjR2r37t1qaGjocMH5l19+qd27dys4ONjJ6QDAMaqrqzV//nzt2bNHUtunGpaUlCgzM1NJSUmyWCxKS0tTUFCQi5MCQM9x+PBhWSwW2Ww2zZgxo0OnJ2dlZWnq1KkqKirq1NougGtDoTkAAACAXm/ixInKzs5WUVGR7rvvPqPjdCuNjY2KiIjo9LzAwEAdOHDA8YGATqiurpbJZGpzwehqTCaTExIBAAAAQGuZmZmqqKig0ByGe+qpp/TCCy9oypQpWrt2rSIjI9WnT582xzY3N2v79u1avny5Tp06pfj4eBenBYDOq62tVWhoqOrr62U2mztU6JiXl6ewsDCVlJTI39/f4CcAgO4pISFB3377rTZv3qyHH364zTEDBw7UmDFjNGbMGD3++OPKzMzUo48+qsTERL377rsuTgz0PhSaAwAAAOj1LBaLxo8fr9OnT3dq3oIFCzR9+nQnpeoeAgICVFBQIJvNpn79+nVojs1mU0FBgUaMGOHkdED7fH19dfLkSR06dEiDBw/u0By73a4HHnhAZWVlTk4HAAAAAFJMTIwaGhqMjgFo8eLFKigo0NatW/XQQw+pb9++GjdunIYPH97yTshms6mmpkaffvqpvvnmG9ntdj3yyCNavHixwekB4Ori4+NVX18vq9Xa7gmeZrNZkZGRiouLk9Vq1dKlS7V69Wpt3LjRdWEBoAfJy8tTRETEFYvM2/LII4/o7rvv1ocffujEZAAuodAcAAAAQK8XERFxTUWjTz/9tBPSdC+zZs1ScnKypk2bptTUVJnN5nbHl5eXKzo6WnV1dXSzguEmTpyonJwc1dTUdOpoRXd3dyemAgAAAID/FR0dbXQEQJLk5uamzZs3Ky0tTVarVYcPH9b+/fu1f//+Nsf/+Mc/VmxsrObPn8+pYAC6hdzcXE2aNKndIvMfio2NVUZGhnJycpwXDAB6uLNnz8rX17fT83x9fdXU1OSERAB+iEJzAAAAAMA1W7lypXbu3KnCwkKFhIQoODi45TjRH3azKi0tVVVVlex2u0JDQ7VixQqD06O3mzhxorKzs1VUVKT77rvP6DgAAAAAAHRpJpNJCxYs0IIFC1RdXa2DBw/q+PHjOnv2rCTJ29tbAQEBGj9+vIKCgowNC6DXuHjxorZt26asrCyVl5fr2LFjOnPmjCRpwIABCgwMlNls1owZMzRjxgy5ubm1eZ/GxkZFRER0+t8PDAzUgQMHrucRAKBXGzlypHbv3q2GhoYOF5x/+eWX2r17t4KDg52cDoBEoTkAAAAA4Dp4eXkpPz9fa9asUWpqqiorK1VZWSlJLd2q7HZ7y3gfHx/FxMQoLi5Onp6ehmS+Xo5auIDxLBaLxo8fr9OnT3dq3oIFCzR9+nQnpQIAAADQG5SVlV3178qoqCiFhIQYnBRoW1BQEMXkAAxXXFysOXPmqLKystV76EtOnjypkydPqrS0VG+99ZZGjRql9PR03XHHHZeNDQgIUEFBgWw2W0sTlaux2WwqKCjQiBEjrvtZAKC3euqpp/TCCy9oypQpWrt2rSIjI9WnT582xzY3N2v79u1avny5Tp06xenJgItQaA4AAAAAuC6enp5KTk5WQkKCCgsL2+1mFR4eLnd3d4MTXztHLlzAeBERESorK+v0vKefftoJaQAAAAD0BtXV1Zo/f7727NkjSW3+bVlSUqLMzEwlJSXJYrEoLS2Ngl4AAH7g8OHDslgsstlsmjFjhmbOnNly2mb//v0lSU1NTS2nbWZkZCgrK0tTp05VUVGRRo8e3ep+s2bNUnJysqZNm6bU1FSZzeZ2//3y8nJFR0errq6OQkcAuA6LFy9WQUGBtm7dqoceekh9+/bVuHHj2jw9+dNPP9U333wju92uRx55RIsXLzY4PdA7UGgOAAAAANdg1apVOnHihEwmk9LS0oyO0yW4u7vLYrHIYrEYHcUpHL1wAQAAAADoXWpraxUaGqr6+nqZzeYO/V2Zl5ensLAwlZSUyN/f3+AnADrvwIED+vrrrxUREWF0FAA9TEJCgr799ltt3rxZDz/8cJtjBg4cqDFjxmjMmDF6/PHHlZmZqUcffVSJiYl69913W41duXKldu7cqcLCQoWEhCg4OLjl5/QPCx1LS0tVVVUlu92u0NBQrVixwunPCwA9lZubmzZv3qy0tDRZrVYdPnxY+/fv1/79+9sc/+Mf/1ixsbGaP39+y+nKAJyLQnMAAAAAuAaZmZmqqKig0LwXcfTCBQAAAACgd4mPj1d9fb2sVquWLFlyxXFms1mRkZGKi4uT1WrV0qVLtXr1am3cuNF1YQEHee6551RUVKQLFy4YHcU4iT4Ovt9px94P6Kby8vIUERFxxXe1bXnkkUd0991368MPP7zsMy8vL+Xn52vNmjVKTU1VZWWlKisrJamlkPH7J5H4+PgoJiZGcXFx8vT0vM6nAYDezWQyacGCBVqwYIGqq6vbPT2Z054A16PQHAAAAACuQUxMjBoaGoyOARdy9MIFAAAAAKB3yc3N1aRJk9otMv+h2NhYZWRkKCcnx3nBACf7fmEmADjK2bNn5evr2+l5vr6+ampqavMzT09PJScnKyEhQYWFhe0WOoaHh8vd3f26ngEAcLmgoCCKyYEuhkJzAAAAALgG0dHRRkeAizlj4QLdz6pVq3TixAlOMwAAAADQaY2NjYqIiOj0vMDAQB04cMDxgQAA6MZGjhyp3bt3q6GhocPvbb/88kvt3r1bwcHB7Y5zd3eXxWKRxWJxQFIAAIDujUJzAAAAAAA6wJkLF+g+MjMzVVFRQaE5AAAAgE4LCAhQQUGBbDab+vXr16E5NptNBQUFGjFihJPTAe27+eabr2lebW2tg5MAwHeeeuopvfDCC5oyZYrWrl2ryMhI9enTp82xzc3N2r59u5YvX65Tp04pPj7exWkBAI524MABff3119e0mRdA51BoDgAAAADfU1ZWpqysLJWXl+vYsWM6c+aMJGnAgAEKDAyU2WxWVFSUQkJCDE4KV2PhApIUExOjhoYGo2MAAAAA6IZmzZql5ORkTZs2TampqTKbze2OLy8vV3R0tOrq6vi7Eoarrq6WyWSS3W7v9FyTyeSERAB6u8WLF6ugoEBbt27VQw89pL59+2rcuHEaPnx4y4Yum82mmpoaffrpp/rmm29kt9v1yCOPaPHixQanBwBcr+eee05FRUW6cOGC0VGAHo9CcwAAAADQd4tl8+fP1549eySpzUWzkpISZWZmKikpSRaLRWlpaQoKCnJxUhiFhQtIUnR0tNERAAAAAHRTK1eu1M6dO1VYWKiQkBAFBwdrwoQJbf5dWVpaqqqqKtntdoWGhmrFihUGp0dv5+vrq5MnT+rQoUMaPHhwh+bY7XY98MADKisrc3I6AL2Rm5ubNm/erLS0NFmtVh0+fFj79+/X/v372xz/4x//WLGxsZo/fz4bYACgh7iWTZAAOo9CcwAAAAC9Xm1trUJDQ1VfXy+z2ayZM2e2LPT2799fktTU1NSy0JuRkaG8vDyFhYWppKRE/v7+Bj8BXIGFCwAAAADA9fDy8lJ+fr7WrFmj1NRUVVZWqrKyUtL/dnz+fqGEj4+PYmJiFBcXJ09PT0MyA5dMnDhROTk5qqmp0ejRozs8z93d3YmpAPR2JpNJCxYs0IIFC1RdXa2DBw/q+PHjOnv2rCTJ29tbAQEBGj9+PE1jAAAArhGF5gAAAAB6vfj4eNXX18tqtWrJkiVXHGc2mxUZGam4uDhZrVYtXbpUq1ev1saNG10XFoZi4aLnKisrU1ZWlsrLy3Xs2DGdOXNGkjRgwAAFBgbKbDYrKipKISEhBicFALjCxYsXtW3btqv+bJgxY4ZmzJghNzc3gxMDALoLT09PJScnKyEhQYWFhe3+XRkeHk6RLrqMiRMnKjs7W0VFRbrvvvuMjgMAlwkKCuKdLAB0QzfffPM1zautrXVwEgBXQqE5AAAAgF4vNzdXkyZNarfI/IdiY2OVkZGhnJwc5wVDl8bCRc9QXV2t+fPna8+ePZLaPmaxpKREmZmZSkpKksViUVpaGv/bA0APVlxcrDlz5qiysrLNnwsnT57UyZMnVVpaqrfeekujRo1Senq67rjjDgPSAgC6K3d3d1ksFlksFqOjAB1isVg0fvx4nT59ulPzFixYoOnTpzspFQAAALq76upqmUymNt/DXQ0nCgOuQaE5AADoUeg6B+BaNDY2KiIiotPzAgMDdeDAAccHAuAStbW1Cg0NVX19vcxms2bOnKkJEyZo+PDh6t+/vySpqalJNTU1Ki0tVUZGhvLy8hQWFqaSkhL5+/sb/AQAAEc7fPiwLBaLbDabZsyY0aGfDVlZWZo6daqKioo0evRog58AAADAOSIiIlRWVtbpeU8//bQT0gDAtTtw4IC+/vrra1oTAAA4nq+vr06ePKlDhw5p8ODBHZpjt9v1wAMPXNPvpwA6j0JzAADQY9B1DsC1CggIUEFBgWw2m/r169ehOTabTQUFBRoxYoST06G7Y+Gi64qPj1d9fb2sVmu7JxqYzWZFRkYqLi5OVqtVS5cu1erVq7Vx40bXhQUAuERCQoK+/fZbbd68WQ8//HCbYwYOHKgxY8ZozJgxevzxx5WZmalHH31UiYmJevfdd12cGAAAAADQGc8995yKiop04cIFo6MAACRNnDhROTk5qqmp6VQTB3d3dyemAvB9FJoDAIAega5zAK7HrFmzlJycrGnTpik1NVVms7nd8eXl5YqOjlZdXZ3i4+NdlLKLSvRx8P06d/xyd8DCRdeVm5urSZMmtVtk/kOxsbHKyMhQTk6O84IBAAyTl5eniIiIKxaZt+WRRx7R3XffrQ8//NCJyQAAAAAAjtJWwyoAgDEmTpyo7OxsFRUV6b777jM6DoA2UGgOAAB6BLrOAbgeK1eu1M6dO1VYWKiQkBAFBwe3bFa51OHcZrO1bFapqqqS3W5XaGioVqxY0e697Xa7/va3v2nbtm06ePCgjh07pjNnzsjNzU2DBw/W2LFjNXXqVD3xxBPy9/d3xePCACxcdE2NjY3X1Gk+MDBQBw4ccHwgAIDhzp49K19f307P8/X1VVNTkxMSAQAAAAAAoDfr6WuNFotF48eP1+nTnWtGtWDBAk2fPt1JqQB8H4XmAACgR6DrHIDr4eXlpfz8fK1Zs0apqamqrKxUZWWlJMlkMklqXSjs4+OjmJgYxcXFydPT84r3/eSTTzR79mwdOnSozULjb775RrW1tdq5c6eSkpK0atUqxcXFOfjpAFxJQECACgoKZLPZWjaVXI3NZlNBQYFGjBjh5HQAACOMHDlSu3fvVkNDQ4cLzr/88kvt3r1bwcHBTk4HAADQvaxatUonTpyQyWRSWlqa0XEA9DA333zzNc2rra1t+wNO7wTQBfWGtcaIiAiVlZV1et7TTz/thDQA2kKhOQAA6BHoOgfgenl6eio5OVkJCQkqLCzUwYMHdfz4cZ09e1aS5O3trYCAAI0fP17h4eFyd3dv937V1dWaMmWKvv76a02ePFlTp07VkCFDdPToUb333ntqbGzU2rVrNW7cOBUWFiotLU0JCQmqrq7Wxo0bXfHI6CSHL1zAcLNmzVJycrKmTZum1NRUmc3mdseXl5crOjpadXV1io+Pd1FKAIArPfXUU3rhhRc0ZcoUrV27VpGRkerTp0+bY5ubm7V9+3YtX75cp06d4mcDAADAD2RmZqqiooJCcwBOUV1dLZPJdE2nSV5qMAMAXRlrjQC6CgrNAQBAj0DXOQCO4u7uLovFIovFcl33SUpK0tdff62UlBRFR0e3+uw3v/mNIiMjlZCQoM8++0z33nuvli1bpp/+9KfatGmTZsyYoRkzZlzXvw/HY+Gi51m5cqV27typwsJChYSEKDg4WBMmTNDw4cNbOpzbbDbV1NSotLRUVVVVstvtCg0N1YoVKwxODwBwhsWLF6ugoEBbt27VQw89pL59+2rcuHFt/mz49NNP9c0338hut+uRRx7R4sWLDU4PAADQtcTExKihocHoGAB6KF9fX508eVKHDh3S4MGDOzTHbrfrgQceuKbOuQDgaqw1AugqKDQHAAA9Al3nAHQ1O3bs0G233XbZix9J6tu3r9avX6+QkBC98847euGFF9S3b1+99dZbCgoK0uuvv87Lny6IhYuex8vLS/n5+VqzZo1SU1NVWVmpyspKSf+7OeD7Gwt8fHwUExOjuLg4eXp6GpIZAOBcbm5u2rx5s9LS0mS1WnX48GHt379f+/fvb3P8j3/8Y8XGxmr+/PlsLAMAAPiBtt6LAYCjTJw4UTk5OaqpqdHo0aM7PO9qp5UCQFfBWiOAroJCcwAA0CPQdQ5AV3Py5ElNnjz5ip9fOk3hUlGrJN1www2aMmXKFQuZYCwWLnomT09PJScnKyEhQYWFhTp48KCOHz+us2fPSpK8vb0VEBCg8ePHKzw8nP89AaAXMJlMWrBggRYsWKDq6up2fzYEBQUZGxYAAAAAeqmJEycqOztbRUVFuu+++4yOAwAOx1rjla1atUonTpyQyWRSWlqa0XGAHo9CcwAA0CPQdQ7oXux2u/72t79p27ZtOnjwoI4dO6YzZ87Izc1NgwcP1tixYzV16lQ98cQT8vf3NzruNRk2bJhKS0t18eJFubm5XfZ5UVGRpO86JH+fj49PSxETuhYWLno2d3d3WSwWWSwWo6MAALqQoKAgiskBAAB+oKysTFlZWSovL295rydJAwYMUGBgoMxms6KiohQSEmJwUgA9mcVi0fjx43X69OlOzVuwYIGmT5/upFQA4DisNV5ZZmamKioqKDQHXIRCcwAA0GPQdQ7oHj755BPNnj1bhw4dkt1uv+zzb775RrW1tdq5c6eSkpK0atUqxcXFGZD0+tx///1644039Oyzz2r9+vUtpytI0uHDh/XMM8/IZDJdVtT6xRdf6MYbb3RxWnQECxcAAAAAAKA3q66u1vz587Vnzx5JavPdXklJiTIzM5WUlCSLxaK0tDTexwNwioiICJWVlXV63tNPP+2ENADgeKw1XllMTIwaGhqMjgH0GhSaAwCAHomuc0DXVF1drSlTpujrr7/W5MmTNXXqVA0ZMkRHjx7Ve++9p8bGRq1du1bjxo1TYWGh0tLSlJCQoOrqam3cuNHo+J0SHx/fctLCli1bdPvtt2vw4ME6duyYioqK1NzcrLvvvrtVAfKZM2dUVFREUXIXxcIFAAC4kgMHDujrr79WRESE0VEAAF1Y0EvbHXq/ai+H3g5oV21trUJDQ1VfXy+z2ayZM2dqwoQJGj58uPr37y9JampqUk1NjUpLS5WRkaG8vDyFhYWppKSk255aCAAAYBTWGq8sOjra6AhAr0KhOQAAAACXSUpK0tdff62UlJTLXgD85je/UWRkpBISEvTZZ5/p3nvv1bJly/TTn/5UmzZt0owZMzRjxgyDknfeTTfdpLy8PM2ePVuffvqpduzY0erzhx9++LKj3Orq6vTiiy/qnnvucWVUAAAAXKfnnntORUVFunDhgtFRAAAAnCI+Pl719fWyWq1asmTJFceZzWZFRkYqLi5OVqtVS5cu1erVq7tdEwkAAACjsdYIoKug0BwAAPRqdJ0DXGvHjh267bbb2txl3rdvX61fv14hISF655139MILL6hv37566623FBQUpNdff71bFZpL0rhx41ReXq7CwkKVlJSoqalJQ4cOVUREhG655ZbLxo8aNUoJCQkGJAUAAMD1stvtRkcAAABwmtzcXE2aNKndIvMfio2NVUZGhnJycpwXDAAAoAfrbWuNZWVlysrKUnl5uY4dO6YzZ85IkgYMGKDAwECZzWZFRUUpJCTE4KRA70KhOQAA6NXoOge41smTJzV58uQrfh4cHCxJqqysbLl2ww03aMqUKdq/f7/T8zlLeHi4wsPDjY4BAAAAAAAAXJPGxsZratgSGBioAwcOOD4QAFyDVatW6cSJEzKZTJd1AQaArqynrzVWV1dr/vz52rNnj6S2GzqUlJQoMzNTSUlJslgsSktLU1BQkIuTAr0TheYAAKDXo+sc4DrDhg1TaWmpLl68KDc3t8s+LyoqkiT5+Pi0uu7j46OzZ8+6JCPgSCxcAADQvdx8883XNK+2ttbBSQAAALqWgIAAFRQUyGazqV+/fh2aY7PZVFBQoBEjRjg5HQB0TGZmpioqKnhfCwBdSG1trUJDQ1VfXy+z2ayZM2dqwoQJGj58uPr37y9JampqUk1NjUpLS5WRkaG8vDyFhYWppKRE/v7+Bj8B0PNRaA4AAADAZe6//3698cYbevbZZ7V+/fpWi1KHDx/WM888I5PJJIvF0mreF198oRtvvNHFaR2noaFB2dnZ7R7zFhkZKV9fX4OTwtFYuAAAoHuprq6WyWS6pg3JJpPJCYkAAAC6hlmzZik5OVnTpk1TamqqzGZzu+PLy8sVHR2turo6xcfHuyglALQvJiZGDQ0NRscAgE7ryWuN8fHxqq+vl9Vq1ZIlS6447tIzxsXFyWq1aunSpVq9erU2btzourBAL0WhOQAA6BHoOgd0D/Hx8dq8ebPS0tK0ZcsW3X777Ro8eLCOHTumoqIiNTc36+6779b06dNb5pw5c0ZFRUWtrnUXp06dUmxsrNLT09Xc3HzFgiWTyaQ+ffpo7ty5evXVVzVo0CDXBoXTsHABGMdut+tvf/ubtm3bpoMHD7a8fHdzc9PgwYM1duxYTZ06VU888QQdTwC08PX11cmTJ3Xo0CENHjy4Q3PsdrseeOABlZWVOTkdAACAcVauXKmdO3eqsLBQISEhCg4Obuk0eamZhM1ma+k0WVVVJbvdrtDQUK1YscLg9ADwnejoaKMjAECn9Ia1xtzcXE2aNKndIvMfio2NVUZGhnJycpwXDEALCs0BAECPQNc5oHu46aablJeXp9mzZ+vTTz/Vjh07Wn3+8MMPX9b1ua6uTi+++KLuuecep+UKemm7Q+9X/Zv/1OnTpxUWFqaKigoNHTpUUVFR7R7zlpWVpU2bNmnv3r3at2+fBg4c6NBMMAYLF4AxPvnkE82ePVuHDh1q8/fDb775RrW1tdq5c6eSkpK0atUqxcXFGZAUQFczceJE5eTkqKamRqNHj+7wPHd3dyemAgAAMJ6Xl5fy8/O1Zs0apaamqrKyUpWVlZL+9x379//+8vHxUUxMjOLi4uTp6WlIZgAAgO6st6w1NjY2KiIiotPzAgMDdeDAAccHAnAZCs0BAECPQNc5oPsYN26cysvLVVhYqJKSEjU1NWno0KGKiIjQLbfcctn4UaNGKSEhwYCk1ycxMVEVFRVatGiR1q1bJw8Pj3bHnz9/XsuWLVNKSooSExNltVpdlBQAepbq6mpNmTJFX3/9tSZPnqypU6dqyJAhOnr0qN577z01NjZq7dq1GjdunAoLC5WWlqaEhARVV1dzxCYATZw4UdnZ2SoqKtJ9991ndBwAAIAuxdPTU8nJyUpISFBhYaEOHjyo48eP6+zZs5Ikb29vBQQEaPz48QoPD2czHgCXKSsrU1ZWlsrLy1tOtZOkAQMGKDAwUGazWVFRUQoJCTE4KQB0XG9ZawwICFBBQYFsNlvLSTlXY7PZVFBQoBEjRjg5HQCJQnMAANBD0HUO6H7Cw8MVHh5udAyn2bJli8aNG6cNGzZ0aLyHh4c2bNigvLw8ZWZmdpuXP70VCxc9RKKPg+932rH3wzVJSkrS119/rZSUlMtOFfjNb36jyMhIJSQk6LPPPtO9996rZcuW6ac//ak2bdqkGTNmaMaMGQYlB9AVWCwWjR8/XqdPd+57+oIFCzR9+nQnpQLgKna7XX/729+0bds2HTx4sOV3fTc3Nw0ePFhjx47V1KlT9cQTT8jf39/ouABgGHd3d1ksFlksFqOjAOjlqqurNX/+fO3Zs0eS2jzZrqSkRJmZmUpKSpLFYlFaWpqCgoJcnBQAOq+3rDXOmjVLycnJmjZtmlJTU2U2m9sdX15erujoaNXV1Sk+Pt5FKYHejUJzAADQI9B1DkBXU1dXp7CwsE7PGzt2rLZu3er4QHAIFi6Arm/Hjh267bbbLisyl6S+fftq/fr1CgkJ0TvvvKMXXnhBffv21VtvvaWgoCC9/vrrFJoDvVxERMQ1nXr19NNPOyENAFf65JNPNHv2bB06dKjN3/O/+eYb1dbWaufOnUpKStKqVasUFxdnQFIAAABIUm1trUJDQ1VfXy+z2ayZM2dqwoQJGj58uPr37y9JampqUk1NjUpLS5WRkaG8vDyFhYWppKSEjYMAurzesta4cuVK7dy5U4WFhQoJCVFwcHDL9/NLHc5tNlvL9/OqqirZ7XaFhoZqxYoVBqcHegcKzQEAQI9A1zmg+2loaFB2dna7HaEjIyPl6+trcNJr4+fnp+LiYl28eFFubm4dmtPc3Kzi4mINGzbMyelwLVi4ALqHkydPavLkyVf8PDg4WJJUWVnZcu2GG27QlClTtH//fqfnAwAAXU91dbWmTJmir7/+WpMnT9bUqVM1ZMgQHT16VO+9954aGxu1du1ajRs3ToWFhUpLS1NCQoKqq6u1ceNGo+MDAAD0SvHx8aqvr5fVatWSJUuuOO7SWkNcXJysVquWLl2q1atX83scgC6vt6w1enl5KT8/X2vWrFFqaqoqKytb3t+bTCZJrRs/+fj4KCYmRnFxcfL09DQkM9DbUGgOAAB6BLrOAd3HqVOnFBsbq/T0dDU3N7fZKU767sVBnz59NHfuXL366qsaNGiQa4NepwcffFApKSl67LHHlJqaqqFDh7Y7vqGhQQsXLtSRI0e0aNEiF6VEZ7BwAXQPw4YNU2lp6RVfvhcVFUn67mX09/n4+Ojs2bMuyQgAALqWpKQkff3110pJSbnsVJTf/OY3ioyMVEJCgj777DPde++9WrZsmX76059q06ZNmjFjBieiAAAAGCA3N1eTJk1q913tD8XGxiojI0M5OTnOCwYADtKb1ho9PT2VnJyshIQEFRYW6uDBgzp+/HjLO3tvb28FBARo/PjxCg8Pl7u7u8GJgd6FQnMAAAAALnP69GmFhYWpoqJCQ4cOVVRUVLsdobOysrRp0ybt3btX+/bt08CBAw1+go5LSkpSdna23n//fWVlZWnKlCntHvNWUFCgc+fOaeTIkUpMTDQ2PNrEwgXQPdx///1644039Oyzz2r9+vUt33Ml6fDhw3rmmWdkMplksVhazfviiy904403ujgtAADoCnbs2KHbbrvtsiJzSerbt6/Wr1+vkJAQvfPOO3rhhRfUt29fvfXWWwoKCtLrr79OoTkAXCe73a6//e1v2rZtmw4ePNhy+qGbm5sGDx6ssWPHaurUqXriiSc4MQ5Ai8bGRkVERHR6XmBgoA4cOOD4QADgYL1xrdHd3V0Wi+Wy9/cAjEWhOQAAAACXSUxMVEVFhRYtWqR169bJw8Oj3fHnz5/XsmXLlJKSosTERFmtVhclvX6DBg3Sxx9/rMWLF+vdd9/Vrl27tHv37jbH2u12ubm5ac6cOVq/fn23697eW7BwAXQP8fHx2rx5s9LS0rRlyxbdfvvtGjx4sI4dO6aioiI1Nzfr7rvv1vTp01vmnDlzRkVFRa2uAUBHrVq1SidOnJDJZFJaWprRcQBcg5MnT2ry5MlX/Dw4OFiSWo7ulqQbbrhBU6ZM0f79+52eDwB6sk8++USzZ8/WoUOH2jz58JtvvlFtba127typpKQkrVq1SnFxcQYkBdDVBAQEqKCgQDabrVWjgfbYbDYVFBRoxIgRTk4HANePtUYAXQWF5gAAAABcZsuWLRo3bpw2bNjQofEeHh7asGGD8vLylJmZ2a0KzSVpyJAhSk9P1yuvvKLc3Nx2j3mbPn26/Pz8DE6M9rBwAXQPN910k/Ly8jR79mx9+umn2rFjR6vPH3744csKQevq6vTiiy/qnnvucWVUAD1EZmamKioqKDQHurFhw4aptLRUFy9elJub22WfFxUVSZJ8fHxaXffx8Wn5+w4A0HnV1dWaMmWKvv76a02ePFlTp07VkCFDdPToUb333ntqbGzU2rVrNW7cOBUWFiotLU0JCQmqrq7Wxo0bjY4PwGCzZs1ScnKypk2bptTUVJnN5nbHl5eXKzo6WnV1dYqPj3dRSgC4Pqw1AugKKDQHAAC9Fl3nANerq6tTWFhYp+eNHTtWW7dudXwgF/Hz89O8efOMjoHrxMIF0H2MGzdO5eXlKiwsVElJiZqamjR06FBFRETolltuuWz8qFGjlJCQYEBSAD1BTEyMGhoajI4B4Drcf//9euONN/Tss89q/fr1rTaWHj58WM8884xMJtNlR3d/8cUXuvHGG12cFgB6jqSkJH399ddKSUlRdHR0q89+85vfKDIyUgkJCfrss8907733atmyZfrpT3+qTZs2acaMGZoxY4ZByQF0BStXrtTOnTtVWFiokJAQBQcHa8KECRo+fHjL73M2m001NTUqLS1VVVWV7Ha7QkNDtWLFCoPTA0DnsNYIwEgUmncxVVVV2r9/v2pqanT+/HkNHjxYo0eP1uTJk+Xl5WV0PAAAehS6zgGu5+fnp+Li4it2iWtLc3OziouLNWzYMCenA9rHwgXQ/YSHhys8PNzoGAB6uB8WRQHofuLj47V582alpaVpy5Ytuv322zV48GAdO3ZMRUVFam5u1t13363p06e3zDlz5oyKiopaXQMAdM6OHTt02223tfn7VN++fbV+/XqFhITonXfe0QsvvKC+ffvqrbfeUlBQkF5//XUKzYFezsvLS/n5+VqzZo1SU1NVWVmpyspKSZLJZJIk2e32lvE+Pj6KiYlRXFycPD09DckMAADQHVFo3kVs3bpVa9asUWlpaZufe3t7a968eUpISJCvr69LMtntdh0+fFj79+/X/v37tW/fPpWXl+uf//xny5gnn3xSf/zjH12SBwAAR6PrHOB6Dz74oFJSUvTYY48pNTVVQ4cObXd8Q0ODFi5cqCNHjmjRokUuSgm0jYULAAAAoGe66aablJeXp9mzZ+vTTz/Vjh07Wn3+8MMPX9akoK6uTi+++KLuueceV0YFgB7l5MmTmjx58hU/Dw4OlqSW9y+SdMMNN2jKlCnav3+/0/MB6Po8PT2VnJyshIQEFRYW6uDBgzp+/LjOnj0r6btam4CAAI0fP17h4eFyd3c3ODEAAED3Q6G5wc6dO6enn35a//3f/93uuLNnz+p3v/ud/vKXv+j9999XRESE0zJt2rRJ//3f/63i4mKdPn3aaf8OAABGo+sc4HpJSUnKzs7W+++/r6ysLE2ZMqXdjtAFBQU6d+6cRo4cqcTERGPDu8CqVat04sQJTlrowli4ALqXhoYGZWdnq7y8XMeOHdOZM2ckSQMGDFBgYKDMZrMiIyNdtqkfQPdSVlamrKysdr+HREVFKSQkxOCkABxh3LhxKi8vV2FhoUpKStTU1KShQ4cqIiJCt9xyy2XjR40apYSEBAOSAkDPMWzYMJWWll7x9MOioiJJ323m/z4fH5+WdzEAIEnu7u6yWCyyWCxGRwEAQ7HWCMAZKDQ30MWLFzVr1ixt27at1fU+ffooICBAPj4+Onr0aKti7y+//FL333+/du3apbCwMKfk2rZtm3bv3u2UewMAAKB7uXjxot5++20VFRVpyJAhmjt3rkaOHCnpu45Dr7zyij766CN99dVXCgoK0qOPPqonn3yyzYUhSRo0aJA+/vhjLV68WO+++6527dp1xd897Xa73NzcNGfOHK1fv16DBg1y1mN2GZmZmaqoqODlTzfAwgXQtZ06dUqxsbFKT09Xc3Nzq9MGvs9kMqlPnz6aO3euXn311V7xswbA1VVXV2v+/Pnas2ePJLX5PaSkpESZmZlKSkqSxWJRWlqagoKCXJwUgDOEh4crPDzc6BgA0OUEvbTdofer/s1/6v7779cbb7yhZ599VuvXr29pRCFJhw8f1jPPPCOTyXTZ+5cvvvhCN954o0PzAAAA9ASsNQJwBgrNDbRu3brLisyfffZZxcfHy9/fX9J3hT3btm3TkiVLdPz4cUnfdXj86U9/qk8//fSy3dvO1r9/fzU1Nbn03wQAoLPoOgc4xj//+U9NmzZNe/bsaSmuefnll5Wdna0f//jHuuuuu1RdXd3y2eHDh/XBBx9oy5Yt2rZtm0wmU5v3HTJkiNLT0/XKK68oNze33Y7Q06dPl5+fn2seuAuIiYlRQ0OD0TEAoFs7ffq0wsLCVFFRoaFDhyoqKqrl9Iz+/ftLkpqamlpOz8jKytKmTZu0d+9e7du3TwMHDjT4CQAYqba2VqGhoaqvr5fZbNbMmTPb/R6SkZGhvLw8hYWFqaSkpOW9LgAAAK4uPj5emzdvVlpamrZs2aLbb79dgwcP1rFjx1RUVKTm5mbdfffdmj59esucM2fOqKioqNU1AAAAfIe1RgDOQKG5QU6ePKlf/epXra79n//zf/TSSy+1uubm5qaHH35YEydObCnkkaSamhpZrVYlJSU5LaOfn5/uvPNOTZw4UXfeeafuvPNO/fa3v3XqvwkAwPWg6xzgWKmpqcrPz9fNN9+smJgY2e12vfbaa/r5z3+uqVOn6tixY4qJidGjjz4qHx8f7d+/X6tXr9b27dv1hz/8QT//+c/bvb+fn5/mzZvnmofpJqKjo42OAADdXmJioioqKrRo0SKtW7dOHh4e7Y4/f/68li1bppSUFCUmJspqtbooKYCuKD4+XvX19bJarVqyZMkVx5nNZkVGRiouLk5Wq1VLly7V6tWrtXHjRteFBeAUDQ0Nys7ObreBQWRkpHx9fQ1Oiqtx9CltABzvpptuUl5enmbPnq1PP/1UO3bsaPX5ww8/fFknzrq6Or344ou65557XBkVAACgW2CtEYAzUGhukLVr17a8nJSkiIgIvfjii1ccf9NNN2njxo267777Wq793//7f/X8889ryJAhDs22evVqpaSkaMSIEQ69LwAAzkTXOcDx3nnnHfXr109///vfW7qKz5o1S6NGjdKbb76pVatWtdqE+G//9m+66667dNttt+lPf/rTVQvNAQBwhi1btmjcuHHasGFDh8Z7eHhow4YNysvLU2ZmJoXmQC+Xm5urSZMmtVtk/kOxsbHKyMhQTk6O84IBcLpTp04pNjZW6enpam5ubrOBgSSZTCb16dNHc+fO1auvvqpBgwa5Nig6xFmntAFwvHHjxqm8vFyFhYUqKSlRU1OThg4dqoiICN1yyy2XjR81apQSEhIMSAoAAAAAvROF5ga4ePGiNm3a1OpaYmLiVV9a3XvvvZoyZYoKCgokfXcs2HvvvafnnnvOofkmTJjg0PsBAOAKdJ0DHO/w4cOaMmVKS5G5JPn7+ysiIkI7duzQ008/fdmcW2+9VWFhYSorK3Nl1C6vrKxMWVlZ7XbEi4qKUkhIiMFJAaD7q6urU1hYWKfnjR07Vlu3bnV8IADdSmNjoyIiIjo9LzAwUAcOHHB8IAAucfr0aYWFhamiokJDhw5VVFRUuw0MsrKytGnTJu3du1f79u3TwIEDDX4C/JCzT2kD4Hjh4eEKDw83OgYAAECXxFojACNRaG6AvXv36ssvv2z5+uabb5bFYunQ3Keffrql0FyStm7d6vBCcwAAuiO6zgGOd+7cOfn4+Fx2/dIC+pVO1hkyZIhsNpvDcqxatUonTpyQyWS67Kjcrq66ulrz58/Xnj17JKnNjnglJSXKzMxUUlKSLBaL0tLSFBQU5OKkANBz+Pn5qbi4WBcvXpSbm1uH5jQ3N6u4uFjDhg1zcjoAXV1AQIAKCgpks9nUr1+/Ds2x2WwqKCjghEigG0tMTFRFRYUWLVqkdevWycPDo93x58+f17Jly5SSkqLExEROROmCOKUNAAAAQE/QK9YaEy9fj76++5127P0AUGhuhO3bt7f6+t///d87fATfv//7v7f6Oj8/X01NTS0dNQAA6K3oOgc43r/+67/q008/vez6pWslJSWX/f+d3W5XWVmZfH19HZYjMzNTFRUV3a7QvLa2VqGhoaqvr5fZbNbMmTPb7YiXkZGhvLw8hYWFqaSkRP7+/gY/AQB0Tw8++KBSUlL02GOPKTU1VUOHDm13fENDgxYuXKgjR45o0aJFLkoJoKuaNWuWkpOTNW3aNKWmpspsNrc7vry8XNHR0aqrq1N8fLyLUgJwtC1btmjcuHHasGFDh8Z7eHhow4YNysvLU2ZmJoXmXRCntAHdT0NDg7Kzs9vt0hkZGenQ944AAABdGWuNALoKCs0N8MNitsmTJ3d4rr+/v4KCglRdXS3pu64Zhw4d0p133unAhAAAdD90nQMcb+rUqfrTn/6kdevWadmyZZKkl19+WZ999pkmTJig559/Xrm5uS2Ltna7XXFxcTpy5Igefvhhh+WIiYlRQ0ODw+7nKvHx8aqvr5fVam33tIVLi2RxcXGyWq1aunSpVq9erY0bN7ouLAD0IElJScrOztb777+vrKwsTZkypeXl+6XfE202W8vL94KCAp07d04jR45UYmKiseEBGG7lypXauXOnCgsLFRISouDg4Ha/h1RVVclutys0NFQrVqwwOD2Aa1VXV6ewsLBOzxs7dqy2bt3q+EC4bl3llDYAV3fq1CnFxsYqPT1dzc3NbXbplCSTyaQ+ffpo7ty5evXVVzVo0CDXBgUAAHAx1hoBdBUUmhvgs88+a/X1mDFjOjV/zJgxLYXml+5HoTkAoLej6xzgeCtXrlRGRoZeeukl/fKXv5T0XVFNQECAtmzZIrPZrFtuuUWhoaHy8fFRWVmZjh49Kjc3Ny1evNhhOaKjox12L1fKzc3VpEmT2n3x80OxsbHKyMhQTk6O84IBQA83aNAgffzxx1q8eLHeffdd7dq1S7t3725zrN1ul5ubm+bMmaP169dTqABAXl5eys/P15o1a5SamqrKykpVVlZKUsuplN8vfvLx8VFMTIzi4uLk6elpSGYA18/Pz0/FxcW6ePGi3NzcOjSnublZxcXFGjZsmJPT4Vp0lVPaALTv9OnTCgsLU0VFhYYOHaqoqKh2u3RmZWVp06ZN2rt3r/bt29eyeQQAAKAnYq0RQFdBobmLffPNNzp+/Hira53tovrD8RUVFdedCwCA7o6uc4DjjRo1Sjt27FBMTIwOHDggNzc33X333Xr99dc1YsQIbd68WY8++qh27drVMsfT01OvvPLKZYu1vVFjY+M1/XcIDAy87BQkAEDnDBkyROnp6XrllVeUm5urgwcP6vjx4zp79qwkydvbWwEBARo/frymT5/ecjoHAEjf/U6bnJyshIQEFRYWtvs9JDw8XO7u7gYnBnC9HnzwQaWkpOixxx5Tamqqhg4d2u74hoYGLVy4UEeOHNGiRYtclBKd0VVOaQPQvsTERFVUVGjRokVat26dPDw82h1//vx5LVu2TCkpKUpMTJTVanVRUgAAANdjrRFAV0GhuYs1NDS06njj7u6uG2+8sVP3uOmmm1p9XV9f75BsAAB0Z3SdA5xj8uTJKi0tVVNTk9zd3Vst9txzzz2qrKzU9u3bVVNTIz8/v04V65WVlSkrK0vl5eU6duyYzpw5I0kaMGCAAgMDZTabFRUVpZCQEKc8m7MFBASooKBANputZcPL1dhsNhUUFHR6MyoAoG1+fn6aN2+e0TEAdFPu7u6yWCyyWCxGRwHgZElJScrOztb777+vrKwsTZkypd0GBgUFBTp37pxGjhypxMREY8OjTV3llDYA7duyZYvGjRunDRs2dGi8h4eHNmzYoLy8PGVmZlJoDgAAejTWGgF0FRSau9ilrjeX9OvXr6X4raMuHRN2pXv2NPX19fryyy87NedSYSEAoHeh6xzgPD/8HfSSwYMH6/HHH+/UvaqrqzV//nzt2bNHUutNIJeUlJQoMzNTSUlJslgsSktLU1BQUKdzG2nWrFlKTk7WtGnTlJqaKrPZ3O748vJyRUdHq66uTvHx8S5KCQAAAAAYNGiQPv74Yy1evFjvvvuudu3apd27d7c51m63y83NTXPmzNH69es1aNAg14ZFh3BKG9A91NXVKSwsrNPzxo4dq61btzo+EIBuI+il7Q6/Z7WXw28JANeFtUYAXQWF5i72w6JwL6/O/6bat2/fdu/Z07z22mtKSkoyOgYAoBuh6xzQddXW1io0NFT19fUym82aOXNmS5e4S8XsTU1NLV3iMjIylJeXp7CwMJWUlMjf39/gJ+i4lStXaufOnSosLFRISIiCg4Pb7YhXVVUlu92u0NBQrVixwuD0uEyijxPuedrx9wQAAABwTYYMGaL09HS98sorys3NbbeBQWdO84JxnHlKGwDH8PPzU3FxsS5evCg3N7cOzWlublZxcbGGDRvm5HQAAADGYq0RQFdBobmLffvtt62+/v5LrY7y9PRs9fU333xzXZkAAACAq2loaFB2drbKy8t17NgxnTlzRpI0YMAABQYGymw2KzIyUr6+vu3eJz4+XvX19bJarVqyZMkVx126X1xcnKxWq5YuXarVq1dr48aNjnwsp/Ly8lJ+fr7WrFmj1NRUVVZWtpy8c+lUo+93c/fx8VFMTIzi4uIu+50fAOBcq1at0okTJ2QymZSWlmZ0HAAAYCA/Pz/NmzfP6BhwIEee0gbAsR588EGlpKToscceU2pqqoYOHdru+IaGBi1cuFBHjhzRokWLXJQSAADAGKw1AugqKDR3sR92MD9//nyn73Hu3Ll27wkAAAA4yqlTpxQbG6v09HQ1Nze3elnxfSaTSX369NHcuXP16quvXvHo8NzcXE2aNKndIvMfio2NVUZGhnJycq7hCYzl6emp5ORkJSQkqLCwsN2OeOHh4XJ3dzc4MQD0TpmZmaqoqKDQHAAAAABcKCkpSdnZ2Xr//feVlZWlKVOmtNuls6CgQOfOndPIkSOVmJhobHgAAAAXYK0RQFdAobmLeXt7t/r6hx3OO+KHHcx/eM+eZuHChXr00Uc7NaeyslIPPfSQcwIBAAD0EqdPn1ZYWJgqKio0dOhQRUVFtSz0XOoG1tTU1LLQk5WVpU2bNmnv3r3at2+fBg4ceNk9GxsbFRER0eksgYGBOnDgwPU+kmHc3d1lsVhksViMjgIAaENMTIwaGhqMjgEAAAAncNQpbQAcb9CgQfr444+1ePFivfvuu9q1a5d2797d5li73S43NzfNmTNH69evv2KjCwAAgJ6ItUYARqLQ3MV+WBRus9lkt9tbjrPoiKampnbv2dPceOONuvHGG42OAQBwgosXL+rtt99WUVGRhgwZorlz52rkyJGSpJMnT+qVV17RRx99pK+++kpBQUF69NFH9eSTT8rNzc3g5EDvkJiYqIqKCi1atEjr1q2Th4dHu+PPnz+vZcuWKSUlRYmJibJarZeNCQgIUEFBgWw2W0tXoqux2WwqKCjQiBEjruk5AAC4mujoaKMjAACAbmbVqlU6ceIEJ6J0YY4+pQ2AcwwZMkTp6el65ZVXlJub226XzunTp8vPz8/gxAAAAADQu1Bo7mK+vr4ymUwtL7P++c9/qr6+XsOGDevwPb744otWX1OEDQDojv75z39q2rRp2rNnT8vPxZdfflnZ2dn68Y9/rLvuukvV1dUtnx0+fFgffPCBtmzZom3btnVqkxaAa7NlyxaNGzdOGzZs6NB4Dw8PbdiwQXl5ecrMzGyz0HzWrFlKTk7WtGnTlJqaKrPZ3O49y8vLFR0drbq6OsXHx1/TcwAAAAAA4GiZmZmqqKig0LyLcsYpbQCcy8/PT/PmzTM6BgAAAADgByg0d7G+ffsqICBAx44da7l2/PjxThWaHz9+vNXXo0ePdlg+AABcJTU1Vfn5+br55psVExMju92u1157TT//+c81depUHTt2TDExMXr00Ufl4+Oj/fv3a/Xq1dq+fbv+8Ic/6Oc//7nRjwD0eHV1dQoLC+v0vLFjx2rr1q1tfrZy5Urt3LlThYWFCgkJUXBwcMtC76UO5zabrWWht6qqSna7XaGhoVqxYsX1PA4AoIty5ik3ZWVlysrKUnl5uY4dO6YzZ85IkgYMGKDAwECZzWZFRUUpJCTEqc8IAAB6npiYGDU0NBgdA1fgjFPaAAAAAAAAeiMKzQ0wevToVoXmhw4d0p133tnh+Z999tll9wMAoLt555131K9fP/39739vOepy1qxZGjVqlN58802tWrVKSUlJLeP/7d/+TXfddZduu+02/elPf6LQHHABPz8/FRcX6+LFix0q5pOk5uZmFRcXX3EjpZeXl/Lz87VmzRqlpqaqsrJSlZWVktRyUsH3j7L28fFRTEyM4uLi5OnpeZ1PBADoapx1yk11dbXmz5+vPXv2SGr9s+WSkpISZWZmKikpSRaLRWlpaQoKCnLOgwIAgB4nOjra6AhohzNOaQMAAAAAAOiNKDQ3wG233aYPPvig5eu9e/fqySef7NDcEydOqLq6uuVrd3d3jRkzxtERAQBwusOHD2vKlCktReaS5O/vr4iICO3YsUNPP/30ZXNuvfVWhYWFqayszJVRgV7rwQcfVEpKih577DGlpqZq6NCh7Y5vaGjQwoULdeTIES1atOiK4zw9PZWcnKyEhAQVFhbq4MGDOn78uM6ePStJ8vb2VkBAgMaPH6/w8HC5u7s79LkAAF2HM065qa2tVWhoqOrr62U2mzVz5syW0zP69+8vSWpqamo5PSMjI0N5eXkKCwtTSUmJ/P39Xf2fAQAAAA7mjFPaAHQNq1at0okTJ2QymZSWlmZ0HAAAAADo8Sg0N8ADDzygl19+ueXrXbt2yW63X7EL1/ft2LGj1ddTp06Vt7e3wzMCAOBs586dk4+Pz2XXBw4cKEkaMmRIm/OGDBkim83m1GwAvpOUlKTs7Gy9//77ysrK0pQpU1oK9fr16ydJstlsLYV6BQUFOnfunEaOHKnExMSr3t/d3V0Wi0UWi8W5DwIA6LKcccpNfHy86uvrZbVatWTJkiv+22azWZGRkYqLi5PVatXSpUu1evVqbdy40eHPCaB7CHppu0PvV+3l0NsBcJGysjJlZWWpvLxcx44d05kzZyRJAwYMUGBgoMxms6KiohQSEmJwUrTHGae0AegaMjMzVVFRQaE5AAAAALgIheYGmDx5snx9fdXQ0CBJOnLkiPLz8zV16tSrzv3hH8sPPvigUzICAOBs//qv/6pPP/30suuXrpWUlCgiIqLVZ3a7XWVlZfL19XVJRqC3GzRokD7++GMtXrxY7777rnbt2qXdu3e3OdZut8vNzU1z5szR+vXrNWjQINeGBQB0S8445SY3N1eTJk1qt8j8h2JjY5WRkaGcnJxOPwMAAOgZqqurNX/+fO3Zs0fSd3/n/lBJSYkyMzOVlJQki8WitLQ0BQUFuTgpOsJZp7QBMF5MTEzLOjsAAAAAwPkoNDeAm5ub5s2bp1deeaXl2qWXku11Nd+9e7cKCgpavh4wYIB++tOfOjUrAADOMnXqVP3pT3/SunXrtGzZMknSyy+/rM8++0wTJkzQ888/r9zc3JaiI7vdrri4OB05ckQPP/zw5TdMvLw7+nVJPO3Y+wHd1JAhQ5Senq5XXnlFubm5OnjwoI4fP66zZ89Kkry9vRUQEKDx48dr+vTprQoFAQC4GmecctPY2HjZhsWOCAwM1IEDBzo9DwAAdH+1tbUKDQ1VfX29zGazZs6c2XKiV//+/SVJTU1NLSd6ZWRkKC8vT2FhYSopKZG/v7/BT4AfcvYpbQCMEx0dbXQEAAAAAOhVKDQ3yIsvvqjXX3+9pUBnz549evnll/XSSy+1Of6LL77QggULWl1bvHjxVTu6/rBwPS8vTxaL5dqDAwDgICtXrlRGRoZeeukl/fKXv5T03eJOQECAtmzZIrPZrFtuuUWhoaHy8fFRWVmZjh49Kjc3Ny1evNjg9EDv4+fnp3nz5hkdAwDQwzjjlJuAgAAVFBTIZrO1FBFdjc1mU0FBgUaMGNHJJwAAAD1BfHy86uvrZbVa2z0VxWw2KzIyUnFxcbJarVq6dKlWr16tjRs3ui4sOoRT2gAAAAAAAByDQnOD+Pr6auXKlVq5cmXLtRUrVuj48eOKi4tr6X5x8eJF/fWvf9XixYt1/PjxlrH+/v564YUXnJLt22+/1d///vc2Pzty5Eirr0+cOKFdu3a1OXbs2LH613/9V4fnAwD0DKNGjdKOHTsUExOjAwcOyM3NTXfffbdef/11jRgxQps3b9ajjz7a6ueMp6enXnnllWvqUAkAAICux+Gn3EiaNWuWkpOTNW3aNKWmpspsNreboby8XNHR0aqrq1N8fLxjHxAAAHQLubm5mjRpUrtF5j8UGxurjIwM5eTkOC8YrguntAHdS1lZmbKyslReXq5jx47pzJkzkr475TswMFBms1lRUVEKCQkxOCkAAAAA9C4UmhvoxRdf1N69e/W3v/2t5drvf/97/eEPf1BgYKB8fHx09OhRnTp1qtW8vn376r333nNaR4W6ujr9+7//e4fG7tixQzt27Gjzs02bNtH1EgDQrsmTJ6u0tFRNTU1yd3eXh4dHy2f33HOPKisrtX37dtXU1MjPz48FHwAAgB7GGafcrFy5Ujt37lRhYaFCQkIUHBysCRMmaPjw4S0dzm02m2pqalRaWqqqqirZ7XaFhoZqxYoVLnt2AADQdTQ2Nl5TY4PAwEAdOHDA8YHgUJzSBnRt1dXVmj9/vvbs2SPpuw3GP1RSUqLMzEwlJSXJYrEoLS1NQUFBLk4KAAAAAL0TheYGcnNzU0ZGhp566im9++67Ldebm5sv6xx+yZAhQ/T+++8rPDzcVTEBAHC6/v37t3l98ODBevzxx12cBsD1WLVqlU6cOCGTyaS0tDSj4xgn0ccJ9zzt+HsCgMGcccqNl5eX8vPztWbNGqWmpqqyslKVlZWSJJPJJKl14YKPj49iYmIUFxcnT09PJz4tAADoqgICAlRQUCCbzdayMe1qbDabCgoKNGLECCenA4Ceq7a2VqGhoaqvr5fZbNbMmTNbNgpfWjdoampq2SickZGhvLw8hYWFqaSkpOWUcAAAgB7H0WuNrDMCuA4UmhvMy8tLf/7znzVz5kwlJydfsfNF//799eSTTyohIUE33nija0MCAAAAHZSZmamKigoKzQEAHeaMU248PT2VnJyshIQEFRYW6uDBgzp+/LjOnj0rSfL29lZAQIDGjx+v8PBwubu7O/UZAQBA1zZr1iwlJydr2rRpSk1Nldlsbnd8eXm5oqOjVVdXp/j4eBelBICeJz4+XvX19bJarVqyZMkVx5nNZkVGRiouLk5Wq1VLly7V6tWrtXHjRteFBQAAAIBeikLzLuInP/mJfvKTn6iyslL79u3TF198ofPnz2vQoEH68Y9/rPDwcHl5eXX6vm0dLXY1QUFB1zQPAIBr1dDQoOzsbJWXl+vYsWM6c+aMJGnAgAEKDAxseYns6+trcFIAVxMTE6OGhgajYwAAuiFnnHLj7u4ui8Uii8VyHckAAEBPt3LlSu3cuVOFhYUKCQlRcHBwS0fdSx3ObTZbS0fdqqoq2e12hYaGasWKFQanh6NwShvgerm5uZo0aVK7ReY/FBsbq4yMDOXk5DgvGAAAAACgBYXmXczIkSM1cuRIo2MAAOASp06dUmxsrNLT09Xc3HzFjU4mk0l9+vTR3Llz9eqrr2rQoEGuDQqgw6Kjo42OAAAAAABAp3h5eSk/P19r1qxRamqqKisrVVlZKem791JS68Y+Pj4+iomJUVxcnDw9PQ3JDMfjlDbA9RobGxUREdHpeYGBgVc8KRwAAAAA4FgUmgMAAEOcPn1aYWFhqqio0NChQxUVFdXSKepSN8umpqaWTlFZWVnatGmT9u7dq3379mngwIEGPwEAAAAciVNuAACAkTw9PZWcnKyEhAQVFhbq4MGDOn78uM6ePStJ8vb2VkBAgMaPH6/w8HC5u7sbnBiOxiltgOsFBASooKBANput5QSJq7HZbCooKNCIESOcnA4AAAAAIFFoDgAADJKYmKiKigotWrRI69atk4eHR7vjz58/r2XLliklJUWJiYmyWq0uSgpAksrKypSVldVu8V9UVJRCQkIMTgoA6G445QYAAHQl7u7uslgsslgsRkeBi3FKG+B6s2bNUnJysqZNm6bU1FSZzeZ2x5eXlys6Olp1dXWKj493UUoAAAAA6N0oNAcAAIbYsmWLxo0bpw0bNnRovIeHhzZs2KC8vDxlZmZSaA64SHV1tebPn689e/ZIUpvFfyUlJcrMzFRSUpI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", 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" ] }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DuckDB better count: 29\n", + "chDB better count: 14\n", + "DuckDB total time: 5.650859117507935\n", + "chDB total time: 6.016231060028076\n" + ] } ], "source": [ @@ -1484,7 +1545,18 @@ "\n", "\n", "fig.tight_layout()\n", - "plt.show()" + "plt.show()\n", + "\n", + "better = []\n", + "for i in range(len(queries)):\n", + " if duckdb_times[i] < chdb_times[i]:\n", + " better.append(\"DuckDB\")\n", + " else:\n", + " better.append(\"chDB\")\n", + "print(\"DuckDB better count:\", better.count(\"DuckDB\"))\n", + "print(\"chDB better count:\", better.count(\"chDB\"))\n", + "print(\"DuckDB total time:\", sum(duckdb_times))\n", + "print(\"chDB total time:\", sum(chdb_times))\n" ] } ], diff --git a/tests/test_issue229.py b/tests/test_issue229.py new file mode 100644 index 00000000000..92005499e84 --- /dev/null +++ b/tests/test_issue229.py @@ -0,0 +1,62 @@ +import threading +from chdb import session + + +def perform_operations(index): + sess = session.Session() + print(f"Performing operations in session {index}, path = {sess._path}") + + # Create a local database + sess.query("CREATE DATABASE local", "Debug") + + # Create a table within the local database + sess.query( + """ + USE local; + CREATE TABLE IF NOT EXISTS knowledge_base_portal_interface_event + ( + timestamp DateTime64, + company_id Int64, + event_type String, + locale String, + article_id Int64 DEFAULT 0, + ) + ENGINE = MergeTree + ORDER BY (company_id, locale, timestamp) + COMMENT 'This table represents a store of knowledge base portal interface events'; + """ + ) + + # Insert multiple entries into the table + for i in range(15): + sess.query( + f""" + INSERT INTO knowledge_base_portal_interface_event + FORMAT JSONEachRow [{{"company_id": {i+index}, "locale": "en", "timestamp": 1717780952772, "event_type": "article_update", "article_id": 7}},{{"company_id": { + i + index + 100 + }, "locale": "en", "timestamp": 1717780952772, "event_type": "article_update", "article_id": 7}}]""" + ) + + # Retrieve all entries from the table + results = sess.query( + "SELECT * FROM knowledge_base_portal_interface_event", "JSONObjectEachRow" + ) + print("Session Query Result:", results) + + # Cleanup session + sess.cleanup() + + +# Create multiple threads to perform operations +threads = [] +for i in range(5): + threads.append(threading.Thread(target=perform_operations, args=(i,))) + +for thread in threads: + thread.start() + +for thread in threads: + thread.join() + +# for i in range(5): +# perform_operations(i)