use of io.trino.sql.planner.SystemPartitioningHandle.FIXED_HASH_DISTRIBUTION in project trino by trinodb.
the class LogicalPlanner method createTableWriterPlan.
private RelationPlan createTableWriterPlan(Analysis analysis, PlanNode source, List<Symbol> symbols, WriterTarget target, List<String> columnNames, List<ColumnMetadata> columnMetadataList, Optional<TableLayout> writeTableLayout, TableStatisticsMetadata statisticsMetadata) {
Optional<PartitioningScheme> partitioningScheme = Optional.empty();
Optional<PartitioningScheme> preferredPartitioningScheme = Optional.empty();
if (writeTableLayout.isPresent()) {
List<Symbol> partitionFunctionArguments = new ArrayList<>();
writeTableLayout.get().getPartitionColumns().stream().mapToInt(columnNames::indexOf).mapToObj(symbols::get).forEach(partitionFunctionArguments::add);
List<Symbol> outputLayout = new ArrayList<>(symbols);
Optional<PartitioningHandle> partitioningHandle = writeTableLayout.get().getPartitioning();
if (partitioningHandle.isPresent()) {
partitioningScheme = Optional.of(new PartitioningScheme(Partitioning.create(partitioningHandle.get(), partitionFunctionArguments), outputLayout));
} else {
// empty connector partitioning handle means evenly partitioning on partitioning columns
preferredPartitioningScheme = Optional.of(new PartitioningScheme(Partitioning.create(FIXED_HASH_DISTRIBUTION, partitionFunctionArguments), outputLayout));
}
}
verify(columnNames.size() == symbols.size(), "columnNames.size() != symbols.size(): %s and %s", columnNames, symbols);
Map<String, Symbol> columnToSymbolMap = zip(columnNames.stream(), symbols.stream(), SimpleImmutableEntry::new).collect(toImmutableMap(Entry::getKey, Entry::getValue));
Set<Symbol> notNullColumnSymbols = columnMetadataList.stream().filter(column -> !column.isNullable()).map(ColumnMetadata::getName).map(columnToSymbolMap::get).collect(toImmutableSet());
if (!statisticsMetadata.isEmpty()) {
TableStatisticAggregation result = statisticsAggregationPlanner.createStatisticsAggregation(statisticsMetadata, columnToSymbolMap);
StatisticAggregations.Parts aggregations = result.getAggregations().createPartialAggregations(symbolAllocator, plannerContext);
// partial aggregation is run within the TableWriteOperator to calculate the statistics for
// the data consumed by the TableWriteOperator
// final aggregation is run within the TableFinishOperator to summarize collected statistics
// by the partial aggregation from all of the writer nodes
StatisticAggregations partialAggregation = aggregations.getPartialAggregation();
TableFinishNode commitNode = new TableFinishNode(idAllocator.getNextId(), new TableWriterNode(idAllocator.getNextId(), source, target, symbolAllocator.newSymbol("partialrows", BIGINT), symbolAllocator.newSymbol("fragment", VARBINARY), symbols, columnNames, notNullColumnSymbols, partitioningScheme, preferredPartitioningScheme, Optional.of(partialAggregation), Optional.of(result.getDescriptor().map(aggregations.getMappings()::get))), target, symbolAllocator.newSymbol("rows", BIGINT), Optional.of(aggregations.getFinalAggregation()), Optional.of(result.getDescriptor()));
return new RelationPlan(commitNode, analysis.getRootScope(), commitNode.getOutputSymbols(), Optional.empty());
}
TableFinishNode commitNode = new TableFinishNode(idAllocator.getNextId(), new TableWriterNode(idAllocator.getNextId(), source, target, symbolAllocator.newSymbol("partialrows", BIGINT), symbolAllocator.newSymbol("fragment", VARBINARY), symbols, columnNames, notNullColumnSymbols, partitioningScheme, preferredPartitioningScheme, Optional.empty(), Optional.empty()), target, symbolAllocator.newSymbol("rows", BIGINT), Optional.empty(), Optional.empty());
return new RelationPlan(commitNode, analysis.getRootScope(), commitNode.getOutputSymbols(), Optional.empty());
}
use of io.trino.sql.planner.SystemPartitioningHandle.FIXED_HASH_DISTRIBUTION in project trino by trinodb.
the class TestSourcePartitionedScheduler method createStageExecution.
private StageExecution createStageExecution(PlanFragment fragment, NodeTaskMap nodeTaskMap) {
StageId stageId = new StageId(QUERY_ID, 0);
SqlStage stage = SqlStage.createSqlStage(stageId, fragment, ImmutableMap.of(TABLE_SCAN_NODE_ID, new TableInfo(new QualifiedObjectName("test", "test", "test"), TupleDomain.all())), new MockRemoteTaskFactory(queryExecutor, scheduledExecutor), TEST_SESSION, true, nodeTaskMap, queryExecutor, new SplitSchedulerStats());
ImmutableMap.Builder<PlanFragmentId, OutputBufferManager> outputBuffers = ImmutableMap.builder();
outputBuffers.put(fragment.getId(), new PartitionedOutputBufferManager(FIXED_HASH_DISTRIBUTION, 1));
fragment.getRemoteSourceNodes().stream().flatMap(node -> node.getSourceFragmentIds().stream()).forEach(fragmentId -> outputBuffers.put(fragmentId, new PartitionedOutputBufferManager(FIXED_HASH_DISTRIBUTION, 10)));
return createPipelinedStageExecution(stage, outputBuffers.buildOrThrow(), TaskLifecycleListener.NO_OP, new NoOpFailureDetector(), queryExecutor, Optional.of(new int[] { 0 }), 0);
}
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