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feat(rbo,rules): use EI statistics for filter ranges
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@ -6288,44 +6288,23 @@ int processLimitAndOffset(SELECT_LEX& select_lex, gp_walk_info& gwi, SCSEP& csep
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return 0;
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}
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// Loop over available indexes to find and extract corresponding EI column statistics
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// for the first column of the index if any.
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// Statistics is stored in GWI context.
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void extractColumnStatistics(Item_field* ifp, gp_walk_info& gwi)
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{
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// TODO find clear way to check if the field is part of a key
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// if (!ifp->field->part_of_key.is_clear_all())
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// {
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// return;
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// }
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// std::cout << "Processing field item: " << ifp->field_name.str << std::endl;
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// std::cout << "part of a key: " << buf << std::endl;
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// std::cout << "ifp->field->field_index " << ifp->field->field_index << std::endl;
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for (uint j = 0; j < ifp->field->table->s->keys; j++)
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{
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for (uint i = 0; i < ifp->field->table->s->key_info[j].usable_key_parts; i++)
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{
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// std::cout << "key fieldnr " << i << " "
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// << ifp->field->table->s->key_info[j].key_part[i].field->field_name.str << " "
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// << ifp->field->table->s->key_info[j].key_part[i].fieldnr << std::endl;
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if (ifp->field->table->s->key_info[j].key_part[i].fieldnr == ifp->field->field_index + 1)
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{
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// std::cout << "key_info " << j << " key_part " << i << " matched " << std::endl;
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if (i == 0 && ifp->field->read_stats)
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{
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assert(ifp->field->table->s);
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// assert(ifp->field->table->s->db);
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// assert(ifp->field->table->s->table_name);
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// FQCN fqcn({ifp->field->table->s->db.str}, {ifp->field->table->s->table_name.str},
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// {ifp->field->field_name.str});
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// TODO use FQCN as a key type
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std::cout << "Adding column statistics for " << ifp->field->field_name.str << std::endl;
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auto* histogram = dynamic_cast<Histogram_json_hb*>(ifp->field->read_stats->histogram);
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if (histogram)
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{
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std::cout << "Type of histogram object: " << typeid(*histogram).name() << std::endl;
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// std::vector<Histogram_bucket> histogramBuckets = histogram->get_json_histogram();
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// std::cout << "gwi.tableStatisticsMap[{ifp->field->table->s->db.str, "
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// "ifp->field->table->s->table_name.str}][ifp->field->field_name.str].size() "
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// << histogramBuckets.size() << std::endl;
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SchemaAndTableName tableName = {ifp->field->table->s->db.str, ifp->field->table->s->table_name.str};
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gwi.tableStatisticsMap[tableName][ifp->field->field_name.str] = *histogram;
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}
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@ -120,6 +120,12 @@ using ColumnName = std::string;
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using ColumnStatisticsMap = std::unordered_map<ColumnName, Histogram_json_hb>;
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using TableStatisticsMap = std::unordered_map<SchemaAndTableName, ColumnStatisticsMap, SchemaAndTableNameHash>;
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// This structure is used to store MDB AST -> CSEP translation context.
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// There is a column statistics for some columns in a query.
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// As per 23.10.5 "some" means first column of the index in projection list of CSEP
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// satisfies the condition of applyParallelCSEP RBO rule.
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// Note that statistics must be merged from subquery/derived table
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// to the statistics of the outer query.
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struct gp_walk_info
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{
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execplan::CalpontSelectExecutionPlan::ReturnedColumnList returnedCols;
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@ -68,10 +68,6 @@ bool matchParallelCES(execplan::CalpontSelectExecutionPlan& csep)
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execplan::ParseTree* filtersWithNewRangeAddedIfNeeded(execplan::SCSEP& csep, execplan::SimpleColumn& column,
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std::pair<uint64_t, uint64_t>& bound)
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{
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// INV this is SimpleColumn we supply as an argument
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// TODO find the suitable column using EI statistics.
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// auto* column = dynamic_cast<execplan::SimpleColumn*>(csep->returnedCols().front().get());
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// assert(column);
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auto tableKeyColumnLeftOp = new execplan::SimpleColumn(column);
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tableKeyColumnLeftOp->resultType(column.resultType());
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@ -117,13 +113,11 @@ execplan::ParseTree* filtersWithNewRangeAddedIfNeeded(execplan::SCSEP& csep, exe
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// INV nullptr signifies that no suitable column was found
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execplan::SimpleColumn* findSuitableKeyColumn(execplan::CalpontSelectExecutionPlan& csep, optimizer::RBOptimizerContext& ctx)
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{
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std::cout << "findSuitableKeyColumn " << csep.returnedCols().size() << std::endl;
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for (auto& rc : csep.returnedCols())
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{
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auto* simpleColumn = dynamic_cast<execplan::SimpleColumn*>(rc.get());
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if (simpleColumn)
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{
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std::cout << "Found simple column " << simpleColumn->columnName() << std::endl;
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cal_impl_if::SchemaAndTableName schemaAndTableNam = {simpleColumn->schemaName(), simpleColumn->tableName()};
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auto columnStatistics = ctx.gwi.findStatisticsForATable(schemaAndTableNam);
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if (!columnStatistics)
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@ -141,6 +135,7 @@ execplan::SimpleColumn* findSuitableKeyColumn(execplan::CalpontSelectExecutionPl
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return nullptr;
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}
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// TODO char and other numerical types support
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execplan::CalpontSelectExecutionPlan::SelectList makeUnionFromTable(
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execplan::CalpontSelectExecutionPlan& csep, optimizer::RBOptimizerContext& ctx)
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{
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@ -154,13 +149,6 @@ execplan::CalpontSelectExecutionPlan::SelectList makeUnionFromTable(
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return unionVec;
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}
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std::cout << "looking for " << keyColumn->columnName() << " in ctx.gwi.tableStatisticsMap "
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<< " with size " << ctx.gwi.tableStatisticsMap.size() << std::endl;
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for (auto& [k, v] : ctx.gwi.tableStatisticsMap)
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{
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std::cout << "SchemaAndTableName " << k.schema << "." << k.table << " column map size " << v.size() << std::endl;
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}
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cal_impl_if::SchemaAndTableName schemaAndTableName = {keyColumn->schemaName(), keyColumn->tableName()};
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auto tableColumnsStatisticsIt = ctx.gwi.tableStatisticsMap.find(schemaAndTableName);
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if (tableColumnsStatisticsIt == ctx.gwi.tableStatisticsMap.end())
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@ -184,17 +172,13 @@ execplan::CalpontSelectExecutionPlan::SelectList makeUnionFromTable(
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// TODO char and other numerical types support
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std::vector<std::pair<uint64_t, uint64_t>> bounds;
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// TODO need to process tail if number of buckets is not divisible by number of union units
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// TODO non-overlapping buckets if it is a problem at all
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// Loop over buckets to produce filter ranges
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for (size_t i = 0; i < numberOfUnionUnits - 1; ++i)
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{
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auto bucket = columnStatistics.get_json_histogram().begin() + i * numberOfBucketsPerUnionUnit;
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auto endBucket = columnStatistics.get_json_histogram().begin() + (i + 1) * numberOfBucketsPerUnionUnit;
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uint64_t currentLowerBound = *(uint32_t*)bucket->start_value.data();
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uint64_t currentUpperBound = *(uint32_t*)endBucket->start_value.data();
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std::cout << "currentLowerBound " << currentLowerBound << " currentUpperBound " << currentUpperBound
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<< std::endl;
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bounds.push_back({currentLowerBound, currentUpperBound});
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}
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@ -202,12 +186,7 @@ execplan::CalpontSelectExecutionPlan::SelectList makeUnionFromTable(
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// NB despite the fact that currently Histogram_json_hb has the last bucket that has end as its start
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auto lastBucket = columnStatistics.get_json_histogram().begin() + (numberOfUnionUnits - 1) * numberOfBucketsPerUnionUnit;
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uint64_t currentLowerBound = *(uint32_t*)lastBucket->start_value.data();
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std::cout << "lastBucket start_value " << currentLowerBound << std::endl;
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uint64_t currentUpperBound = *(uint32_t*)columnStatistics.get_last_bucket_end_endp().data();
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std::cout << "Histogram end_value " << currentUpperBound << std::endl;
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std::cout << "last currentLowerBound " << currentLowerBound << " last currentUpperBound " << currentUpperBound
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<< std::endl;
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bounds.push_back({currentLowerBound, currentUpperBound});
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for (auto& bound : bounds)
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@ -270,97 +249,13 @@ void applyParallelCES(execplan::CalpontSelectExecutionPlan& csep, RBOptimizerCon
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derivedSCEP->filters(nullptr);
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}
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}
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// Remove the filters as they were pushed down to union units
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// This is inappropriate for EXISTS filter and join conditions
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// csep.filters(nullptr);
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// There must be no derived at this point.
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// Remove the filters if necessary using csep.filters(nullptr) as they were pushed down to union units
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// But this is inappropriate for EXISTS filter and join conditions
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// There must be no derived at this point, so we can replace it with the new derived table list
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csep.derivedTableList(newDerivedTableList);
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// Replace table list with new table list populated with union units
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csep.tableList(newTableList);
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csep.returnedCols(newReturnedColumns);
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}
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// execplan::CalpontSelectExecutionPlan::SelectList makeUnionFromTable_exists(
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// const size_t numberOfLegs, execplan::CalpontSelectExecutionPlan& csep)
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// {
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// execplan::CalpontSelectExecutionPlan::SelectList unionVec;
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// unionVec.reserve(numberOfLegs);
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// std::vector<std::pair<uint64_t, uint64_t>> bounds(
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// {{0, 3000961}, {3000961, std::numeric_limits<uint64_t>::max()}});
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// for (auto bound : bounds)
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// {
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// auto clonedCSEP = csep.cloneWORecursiveSelects();
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// clonedCSEP->filters(nullptr);
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// // Add BETWEEN based on key column range
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// clonedCSEP->filters(filtersWithNewRangeAddedIfNeeded(clonedCSEP, bound));
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// unionVec.push_back(clonedCSEP);
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// }
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// return unionVec;
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// }
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// // TODO: remove applyParallelCES_exists
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// void applyParallelCES_exists(execplan::CalpontSelectExecutionPlan& csep, RBOptimizerContext& ctx)
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// {
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// auto tables = csep.tableList();
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// execplan::CalpontSelectExecutionPlan::TableList newTableList;
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// execplan::CalpontSelectExecutionPlan::SelectList newDerivedTableList;
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// execplan::CalpontSelectExecutionPlan::ReturnedColumnList newReturnedColumns;
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// // ATM Must be only 1 table
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// for (auto& table : tables)
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// {
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// if (!table.isColumnstore())
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// {
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// auto derivedSCEP = csep.cloneWORecursiveSelects();
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// // need to add a level here
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// std::string tableAlias = RewrittenSubTableAliasPrefix + table.schema + "_" + table.table + "_" +
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// std::to_string(ctx.uniqueId);
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// derivedSCEP->location(execplan::CalpontSelectExecutionPlan::FROM);
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// derivedSCEP->subType(execplan::CalpontSelectExecutionPlan::FROM_SUBS);
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// derivedSCEP->derivedTbAlias(tableAlias);
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// // TODO: hardcoded for now
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// size_t parallelFactor = 2;
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// // Create a copy of the current leaf CSEP with additional filters to partition the key column
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// auto additionalUnionVec = makeUnionFromTable_exists(parallelFactor, csep);
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// derivedSCEP->unionVec().insert(derivedSCEP->unionVec().end(), additionalUnionVec.begin(),
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// additionalUnionVec.end());
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// size_t colPosition = 0;
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// // change parent to derived table columns
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// for (auto& rc : csep.returnedCols())
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// {
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// auto rcCloned = boost::make_shared<execplan::SimpleColumn>(*rc);
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// // TODO timezone and result type are not copied
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// // TODO add specific ctor for this functionality
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// rcCloned->tableName("");
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// rcCloned->schemaName("");
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// rcCloned->tableAlias(tableAlias);
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// rcCloned->colPosition(colPosition++);
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// rcCloned->resultType(rc->resultType());
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// newReturnedColumns.push_back(rcCloned);
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// }
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// newDerivedTableList.push_back(derivedSCEP);
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// execplan::CalpontSystemCatalog::TableAliasName tn = execplan::make_aliasview("", "", tableAlias, "");
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// newTableList.push_back(tn);
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// // Remove the filters as they were pushed down to union units
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// // This is inappropriate for EXISTS filter and join conditions
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// // TODO if needed
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// derivedSCEP->filters(nullptr);
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// }
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// }
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// // Remove the filters as they were pushed down to union units
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// // This is inappropriate for EXISTS filter and join conditions
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// // csep.filters(nullptr);
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// // There must be no derived at this point.
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// csep.derivedTableList(newDerivedTableList);
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// // Replace table list with new table list populated with union units
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// csep.tableList(newTableList);
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// csep.returnedCols(newReturnedColumns);
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// }
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} // namespace optimizer
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