somu-imply commented on code in PR #15470: URL: https://github.com/apache/druid/pull/15470#discussion_r1540546269
########## extensions-core/multi-stage-query/src/main/java/org/apache/druid/msq/querykit/WindowOperatorQueryFrameProcessor.java: ########## @@ -0,0 +1,544 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.druid.msq.querykit; + +import com.fasterxml.jackson.databind.ObjectMapper; +import com.google.common.collect.Iterables; +import it.unimi.dsi.fastutil.ints.IntSet; +import org.apache.druid.frame.Frame; +import org.apache.druid.frame.channel.FrameWithPartition; +import org.apache.druid.frame.channel.ReadableFrameChannel; +import org.apache.druid.frame.channel.WritableFrameChannel; +import org.apache.druid.frame.processor.FrameProcessor; +import org.apache.druid.frame.processor.FrameProcessors; +import org.apache.druid.frame.processor.FrameRowTooLargeException; +import org.apache.druid.frame.processor.ReturnOrAwait; +import org.apache.druid.frame.read.FrameReader; +import org.apache.druid.frame.util.SettableLongVirtualColumn; +import org.apache.druid.frame.write.FrameWriter; +import org.apache.druid.frame.write.FrameWriterFactory; +import org.apache.druid.java.util.common.Unit; +import org.apache.druid.java.util.common.logger.Logger; +import org.apache.druid.msq.exec.Limits; +import org.apache.druid.msq.indexing.error.MSQException; +import org.apache.druid.msq.indexing.error.TooManyRowsInAWindowFault; +import org.apache.druid.msq.util.MultiStageQueryContext; +import org.apache.druid.query.groupby.ResultRow; +import org.apache.druid.query.operator.NaivePartitioningOperatorFactory; +import org.apache.druid.query.operator.OffsetLimit; +import org.apache.druid.query.operator.Operator; +import org.apache.druid.query.operator.OperatorFactory; +import org.apache.druid.query.operator.WindowOperatorQuery; +import org.apache.druid.query.rowsandcols.ConcatRowsAndColumns; +import org.apache.druid.query.rowsandcols.LazilyDecoratedRowsAndColumns; +import org.apache.druid.query.rowsandcols.MapOfColumnsRowsAndColumns; +import org.apache.druid.query.rowsandcols.RowsAndColumns; +import org.apache.druid.query.rowsandcols.concrete.RowBasedFrameRowsAndColumns; +import org.apache.druid.query.rowsandcols.semantic.ColumnSelectorFactoryMaker; +import org.apache.druid.segment.ColumnSelectorFactory; +import org.apache.druid.segment.ColumnValueSelector; +import org.apache.druid.segment.Cursor; +import org.apache.druid.segment.VirtualColumn; +import org.apache.druid.segment.VirtualColumns; +import org.apache.druid.segment.column.RowSignature; + +import javax.annotation.Nullable; +import java.io.Closeable; +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Objects; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.function.Supplier; + +public class WindowOperatorQueryFrameProcessor implements FrameProcessor<Object> +{ + private static final Logger log = new Logger(WindowOperatorQueryFrameProcessor.class); + private final WindowOperatorQuery query; + + private final List<OperatorFactory> operatorFactoryList; + private final ObjectMapper jsonMapper; + private final RowSignature outputStageSignature; + private final ArrayList<RowsAndColumns> frameRowsAndCols; + private final ArrayList<RowsAndColumns> resultRowAndCols; + private final ReadableFrameChannel inputChannel; + private final WritableFrameChannel outputChannel; + private final FrameWriterFactory frameWriterFactory; + private final FrameReader frameReader; + private final SettableLongVirtualColumn partitionBoostVirtualColumn; + private final ArrayList<ResultRow> objectsOfASingleRac; + private final int maxRowsMaterialized; + List<Integer> partitionColsIndex; + private long currentAllocatorCapacity; // Used for generating FrameRowTooLargeException if needed + private Cursor frameCursor = null; + private Supplier<ResultRow> rowSupplierFromFrameCursor; + private ResultRow outputRow = null; + private FrameWriter frameWriter = null; + private boolean isOverEmpty; + + public WindowOperatorQueryFrameProcessor( + WindowOperatorQuery query, + ReadableFrameChannel inputChannel, + WritableFrameChannel outputChannel, + FrameWriterFactory frameWriterFactory, + FrameReader frameReader, + ObjectMapper jsonMapper, + final List<OperatorFactory> operatorFactoryList, + final RowSignature rowSignature, + final boolean isOverEmpty + ) + { + this.inputChannel = inputChannel; + this.outputChannel = outputChannel; + this.frameWriterFactory = frameWriterFactory; + this.partitionBoostVirtualColumn = new SettableLongVirtualColumn(QueryKitUtils.PARTITION_BOOST_COLUMN); + this.operatorFactoryList = operatorFactoryList; + this.outputStageSignature = rowSignature; + this.jsonMapper = jsonMapper; + this.frameReader = frameReader; + this.query = query; + this.frameRowsAndCols = new ArrayList<>(); + this.resultRowAndCols = new ArrayList<>(); + this.objectsOfASingleRac = new ArrayList<>(); + this.partitionColsIndex = new ArrayList<>(); + this.isOverEmpty = isOverEmpty; + if (query.context() != null && query.context() + .containsKey(MultiStageQueryContext.MAX_ROWS_MATERIALIZED_IN_WINDOW)) { + maxRowsMaterialized = (int) query.context().get(MultiStageQueryContext.MAX_ROWS_MATERIALIZED_IN_WINDOW); + } else { + maxRowsMaterialized = Limits.MAX_ROWS_MATERIALIZED_IN_WINDOW; + } + } + + private static VirtualColumns makeVirtualColumnsForFrameWriter( + @Nullable final VirtualColumn partitionBoostVirtualColumn, + final ObjectMapper jsonMapper, + final WindowOperatorQuery query + ) + { + List<VirtualColumn> virtualColumns = new ArrayList<>(); + + virtualColumns.add(partitionBoostVirtualColumn); + final VirtualColumn segmentGranularityVirtualColumn = + QueryKitUtils.makeSegmentGranularityVirtualColumn(jsonMapper, query); + if (segmentGranularityVirtualColumn != null) { + virtualColumns.add(segmentGranularityVirtualColumn); + } + + return VirtualColumns.create(virtualColumns); + } + + @Override + public List<ReadableFrameChannel> inputChannels() + { + return Collections.singletonList(inputChannel); + } + + @Override + public List<WritableFrameChannel> outputChannels() + { + return Collections.singletonList(outputChannel); + } + + @Override + public ReturnOrAwait<Object> runIncrementally(IntSet readableInputs) + { + /* + * + * PARTITION BY A ORDER BY B + * + * Frame 1 -> rac1 + * A B + * 1, 2 + * 1, 3 + * 2, 1 --> key changed + * 2, 2 + * + * + * Frame 2 -> rac2 + * 3, 1 --> key changed + * 3, 2 + * 3, 3 + * 3, 4 + * + * Frame 3 -> rac3 + * + * 3, 5 + * 3, 6 + * 4, 1 --> key changed + * 4, 2 + * + * In case of empty OVER clause, all these racs need to be added to a single rows and columns + * to be processed. The way we can do this is to use a ConcatRowsAndColumns + * ConcatRC [rac1, rac2, rac3] + * Run all ops on this + * + * + * The flow would look like: + * 1. Validate if the operator has an empty OVER clause + * 2. If 1 is true make a giant rows and columns (R&C) using concat as shown above + * Let all operators run amok on that R&C + * 3. If 1 is false + * Read a frame + * keep the older row in a class variable + * check row by row and compare current with older row to check if partition boundary is reached + * when frame partition by changes + * create R&C for those particular set of columns, they would have the same partition key + * output will be a single R&C + * write to output channel + * + * + * Future thoughts: {@link https://github.com/apache/druid/issues/16126} + * + * 1. We are writing 1 partition to each frame in this way. In case of low cardinality data + * we will me making a large number of small frames. We can have a check to keep size of frame to a value + * say 20k rows and keep on adding to the same pending frame and not create a new frame + * + * 2. Current approach with R&C and operators materialize a single R&C for processing. In case of data + * with high cardinality a single R&C might be too big to consume. Same for the case of empty OVER() clause + * Most of the window operations like SUM(), RANK(), RANGE() etc. can be made with 2 passes of the data. + * We might think to reimplement them in the MSQ way so that we do not have to materialize so much data + */ + + // Phase 1 of the execution + // eagerly validate presence of empty OVER() clause + if (isOverEmpty) { + // if OVER() found + // have to bring all data to a single executor for processing + // convert each frame to rac + // concat all the racs to make a giant rac + // let all operators run on the giant rac when channel is finished + if (inputChannel.canRead()) { + final Frame frame = inputChannel.read(); + convertRowFrameToRowsAndColumns(frame); + } else if (inputChannel.isFinished()) { + runAllOpsOnMultipleRac(frameRowsAndCols); + return ReturnOrAwait.returnObject(Unit.instance()); + } else { + return ReturnOrAwait.awaitAll(inputChannels().size()); + } + return ReturnOrAwait.runAgain(); + } else { + // Aha, you found a PARTITION BY and maybe ORDER BY TO + // PARTITION BY can also be on multiple keys + // typically the last stage would already partition and sort for you + // figure out frame boundaries and convert each distinct group to a rac + // then run the windowing operator only on each rac + if (frameCursor == null || frameCursor.isDone()) { + if (readableInputs.isEmpty()) { + return ReturnOrAwait.awaitAll(1); + } else if (inputChannel.canRead()) { + final Frame frame = inputChannel.read(); + frameCursor = FrameProcessors.makeCursor(frame, frameReader); + final ColumnSelectorFactory frameColumnSelectorFactory = frameCursor.getColumnSelectorFactory(); + partitionColsIndex = findPartitionColumns(frameReader.signature()); + final Supplier<Object>[] fieldSuppliers = new Supplier[frameReader.signature().size()]; + for (int i = 0; i < fieldSuppliers.length; i++) { + final ColumnValueSelector<?> selector = + frameColumnSelectorFactory.makeColumnValueSelector(frameReader.signature().getColumnName(i)); + fieldSuppliers[i] = selector::getObject; + + } + rowSupplierFromFrameCursor = () -> { + final ResultRow row = ResultRow.create(fieldSuppliers.length); + for (int i = 0; i < fieldSuppliers.length; i++) { + row.set(i, fieldSuppliers[i].get()); + } + return row; + }; + } else if (inputChannel.isFinished()) { + // reaached end of channel + // if there is data remaining + // write it into a rac + // and run operators on it + if (!objectsOfASingleRac.isEmpty()) { + if (objectsOfASingleRac.size() > maxRowsMaterialized) { + throw new MSQException(new TooManyRowsInAWindowFault(objectsOfASingleRac.size(), maxRowsMaterialized)); + } + RowsAndColumns rac = MapOfColumnsRowsAndColumns.fromResultRow( + objectsOfASingleRac, + frameReader.signature() + ); + runAllOpsOnSingleRac(rac); + objectsOfASingleRac.clear(); + } + return ReturnOrAwait.returnObject(Unit.instance()); + } else { + return ReturnOrAwait.runAgain(); + } + } + while (!frameCursor.isDone()) { + final ResultRow currentRow = rowSupplierFromFrameCursor.get(); + if (outputRow == null) { + outputRow = currentRow; + objectsOfASingleRac.add(currentRow); + } else if (comparePartitionKeys(outputRow, currentRow, partitionColsIndex)) { + // if they have the same partition key + // keep adding them + objectsOfASingleRac.add(currentRow); + } else { + // key change noted + // create rac from the rows seen before + // run the operators on these rows and columns + // clean up the object to hold the new rows only + if (objectsOfASingleRac.size() > maxRowsMaterialized) { + throw new MSQException(new TooManyRowsInAWindowFault( + objectsOfASingleRac.size(), + maxRowsMaterialized + )); + } + RowsAndColumns rac = MapOfColumnsRowsAndColumns.fromResultRow( + objectsOfASingleRac, + frameReader.signature() + ); + runAllOpsOnSingleRac(rac); + objectsOfASingleRac.clear(); + outputRow = currentRow.copy(); + return ReturnOrAwait.runAgain(); + } + frameCursor.advance(); + } + } + return ReturnOrAwait.runAgain(); + } + + /** + * @param singleRac Use this {@link RowsAndColumns} as a single input for the operators to be run + */ + private void runAllOpsOnSingleRac(RowsAndColumns singleRac) + { + Operator op = new Operator() + { + @Nullable + @Override + public Closeable goOrContinue(Closeable continuationObject, Receiver receiver) + { + receiver.push(singleRac); + if (singleRac.numRows() > maxRowsMaterialized) { + throw new MSQException(new TooManyRowsInAWindowFault(singleRac.numRows(), maxRowsMaterialized)); + } + receiver.completed(); + return null; + } + }; + runOperatorsAfterThis(op); + } + + /** + * @param listOfRacs Concat this list of {@link RowsAndColumns} to a {@link ConcatRowsAndColumns} to use as a single input for the operators to be run + */ + private void runAllOpsOnMultipleRac(ArrayList<RowsAndColumns> listOfRacs) + { + Operator op = new Operator() + { + @Nullable + @Override + public Closeable goOrContinue(Closeable continuationObject, Receiver receiver) + { + RowsAndColumns rac = new ConcatRowsAndColumns(listOfRacs); + if (rac.numRows() > maxRowsMaterialized) { + throw new MSQException(new TooManyRowsInAWindowFault(rac.numRows(), maxRowsMaterialized)); + } + receiver.push(rac); + receiver.completed(); + return null; + } + }; + runOperatorsAfterThis(op); + } + + /** + * @param op Base operator for the operators to be run. Other operators are wrapped under this to run + */ + private void runOperatorsAfterThis(Operator op) + { + for (OperatorFactory of : operatorFactoryList) { + op = of.wrap(op); + } + Operator.go(op, new Operator.Receiver() + { + @Override + public Operator.Signal push(RowsAndColumns rac) + { + resultRowAndCols.add(rac); + return Operator.Signal.GO; + } + + @Override + public void completed() + { + try { + flushAllRowsAndCols(resultRowAndCols); + } + catch (IOException e) { + throw new RuntimeException(e); + } + finally { + resultRowAndCols.clear(); + } + } + }); + } + + /** + * @param resultRowAndCols Flush the list of {@link RowsAndColumns} to a frame + * @throws IOException + */ + private void flushAllRowsAndCols(ArrayList<RowsAndColumns> resultRowAndCols) throws IOException + { + RowsAndColumns rac = new ConcatRowsAndColumns(resultRowAndCols); + AtomicInteger rowId = new AtomicInteger(0); + createFrameWriterIfNeeded(rac, rowId); + writeRacToFrame(rac, rowId); + } + + /** + * @param rac The frame writer to write this {@link RowsAndColumns} object + * @param rowId RowId to get the column selector factory from the {@link RowsAndColumns} object + */ + private void createFrameWriterIfNeeded(RowsAndColumns rac, AtomicInteger rowId) + { + if (frameWriter == null) { + final ColumnSelectorFactoryMaker csfm = ColumnSelectorFactoryMaker.fromRAC(rac); + final ColumnSelectorFactory frameWriterColumnSelectorFactory = makeVirtualColumnsForFrameWriter( + partitionBoostVirtualColumn, + jsonMapper, + query + ).wrap(csfm.make(rowId)); + frameWriter = frameWriterFactory.newFrameWriter(frameWriterColumnSelectorFactory); + currentAllocatorCapacity = frameWriterFactory.allocatorCapacity(); + } + } + + /** + * @param rac {@link RowsAndColumns} to be written to frame + * @param rowId Counter to keep track of how many rows are added + * @throws IOException + */ + public void writeRacToFrame(RowsAndColumns rac, AtomicInteger rowId) throws IOException + { + final int numRows = rac.numRows(); + rowId.set(0); + while (rowId.get() < numRows) { + final boolean didAddToFrame = frameWriter.addSelection(); + if (didAddToFrame) { + incrementBoostColumn(); Review Comment: boosting has been removed now ########## extensions-core/multi-stage-query/src/main/java/org/apache/druid/msq/querykit/WindowOperatorQueryFrameProcessor.java: ########## @@ -0,0 +1,544 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +package org.apache.druid.msq.querykit; + +import com.fasterxml.jackson.databind.ObjectMapper; +import com.google.common.collect.Iterables; +import it.unimi.dsi.fastutil.ints.IntSet; +import org.apache.druid.frame.Frame; +import org.apache.druid.frame.channel.FrameWithPartition; +import org.apache.druid.frame.channel.ReadableFrameChannel; +import org.apache.druid.frame.channel.WritableFrameChannel; +import org.apache.druid.frame.processor.FrameProcessor; +import org.apache.druid.frame.processor.FrameProcessors; +import org.apache.druid.frame.processor.FrameRowTooLargeException; +import org.apache.druid.frame.processor.ReturnOrAwait; +import org.apache.druid.frame.read.FrameReader; +import org.apache.druid.frame.util.SettableLongVirtualColumn; +import org.apache.druid.frame.write.FrameWriter; +import org.apache.druid.frame.write.FrameWriterFactory; +import org.apache.druid.java.util.common.Unit; +import org.apache.druid.java.util.common.logger.Logger; +import org.apache.druid.msq.exec.Limits; +import org.apache.druid.msq.indexing.error.MSQException; +import org.apache.druid.msq.indexing.error.TooManyRowsInAWindowFault; +import org.apache.druid.msq.util.MultiStageQueryContext; +import org.apache.druid.query.groupby.ResultRow; +import org.apache.druid.query.operator.NaivePartitioningOperatorFactory; +import org.apache.druid.query.operator.OffsetLimit; +import org.apache.druid.query.operator.Operator; +import org.apache.druid.query.operator.OperatorFactory; +import org.apache.druid.query.operator.WindowOperatorQuery; +import org.apache.druid.query.rowsandcols.ConcatRowsAndColumns; +import org.apache.druid.query.rowsandcols.LazilyDecoratedRowsAndColumns; +import org.apache.druid.query.rowsandcols.MapOfColumnsRowsAndColumns; +import org.apache.druid.query.rowsandcols.RowsAndColumns; +import org.apache.druid.query.rowsandcols.concrete.RowBasedFrameRowsAndColumns; +import org.apache.druid.query.rowsandcols.semantic.ColumnSelectorFactoryMaker; +import org.apache.druid.segment.ColumnSelectorFactory; +import org.apache.druid.segment.ColumnValueSelector; +import org.apache.druid.segment.Cursor; +import org.apache.druid.segment.VirtualColumn; +import org.apache.druid.segment.VirtualColumns; +import org.apache.druid.segment.column.RowSignature; + +import javax.annotation.Nullable; +import java.io.Closeable; +import java.io.IOException; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Objects; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.function.Supplier; + +public class WindowOperatorQueryFrameProcessor implements FrameProcessor<Object> +{ + private static final Logger log = new Logger(WindowOperatorQueryFrameProcessor.class); + private final WindowOperatorQuery query; + + private final List<OperatorFactory> operatorFactoryList; + private final ObjectMapper jsonMapper; + private final RowSignature outputStageSignature; + private final ArrayList<RowsAndColumns> frameRowsAndCols; + private final ArrayList<RowsAndColumns> resultRowAndCols; + private final ReadableFrameChannel inputChannel; + private final WritableFrameChannel outputChannel; + private final FrameWriterFactory frameWriterFactory; + private final FrameReader frameReader; + private final SettableLongVirtualColumn partitionBoostVirtualColumn; + private final ArrayList<ResultRow> objectsOfASingleRac; + private final int maxRowsMaterialized; + List<Integer> partitionColsIndex; + private long currentAllocatorCapacity; // Used for generating FrameRowTooLargeException if needed + private Cursor frameCursor = null; + private Supplier<ResultRow> rowSupplierFromFrameCursor; + private ResultRow outputRow = null; + private FrameWriter frameWriter = null; + private boolean isOverEmpty; + + public WindowOperatorQueryFrameProcessor( + WindowOperatorQuery query, + ReadableFrameChannel inputChannel, + WritableFrameChannel outputChannel, + FrameWriterFactory frameWriterFactory, + FrameReader frameReader, + ObjectMapper jsonMapper, + final List<OperatorFactory> operatorFactoryList, + final RowSignature rowSignature, + final boolean isOverEmpty + ) + { + this.inputChannel = inputChannel; + this.outputChannel = outputChannel; + this.frameWriterFactory = frameWriterFactory; + this.partitionBoostVirtualColumn = new SettableLongVirtualColumn(QueryKitUtils.PARTITION_BOOST_COLUMN); + this.operatorFactoryList = operatorFactoryList; + this.outputStageSignature = rowSignature; + this.jsonMapper = jsonMapper; + this.frameReader = frameReader; + this.query = query; + this.frameRowsAndCols = new ArrayList<>(); + this.resultRowAndCols = new ArrayList<>(); + this.objectsOfASingleRac = new ArrayList<>(); + this.partitionColsIndex = new ArrayList<>(); + this.isOverEmpty = isOverEmpty; + if (query.context() != null && query.context() + .containsKey(MultiStageQueryContext.MAX_ROWS_MATERIALIZED_IN_WINDOW)) { + maxRowsMaterialized = (int) query.context().get(MultiStageQueryContext.MAX_ROWS_MATERIALIZED_IN_WINDOW); + } else { + maxRowsMaterialized = Limits.MAX_ROWS_MATERIALIZED_IN_WINDOW; + } + } + + private static VirtualColumns makeVirtualColumnsForFrameWriter( + @Nullable final VirtualColumn partitionBoostVirtualColumn, + final ObjectMapper jsonMapper, + final WindowOperatorQuery query + ) + { + List<VirtualColumn> virtualColumns = new ArrayList<>(); + + virtualColumns.add(partitionBoostVirtualColumn); + final VirtualColumn segmentGranularityVirtualColumn = + QueryKitUtils.makeSegmentGranularityVirtualColumn(jsonMapper, query); + if (segmentGranularityVirtualColumn != null) { + virtualColumns.add(segmentGranularityVirtualColumn); + } + + return VirtualColumns.create(virtualColumns); + } + + @Override + public List<ReadableFrameChannel> inputChannels() + { + return Collections.singletonList(inputChannel); + } + + @Override + public List<WritableFrameChannel> outputChannels() + { + return Collections.singletonList(outputChannel); + } + + @Override + public ReturnOrAwait<Object> runIncrementally(IntSet readableInputs) + { + /* + * + * PARTITION BY A ORDER BY B + * + * Frame 1 -> rac1 + * A B + * 1, 2 + * 1, 3 + * 2, 1 --> key changed + * 2, 2 + * + * + * Frame 2 -> rac2 + * 3, 1 --> key changed + * 3, 2 + * 3, 3 + * 3, 4 + * + * Frame 3 -> rac3 + * + * 3, 5 + * 3, 6 + * 4, 1 --> key changed + * 4, 2 + * + * In case of empty OVER clause, all these racs need to be added to a single rows and columns + * to be processed. The way we can do this is to use a ConcatRowsAndColumns + * ConcatRC [rac1, rac2, rac3] + * Run all ops on this + * + * + * The flow would look like: + * 1. Validate if the operator has an empty OVER clause + * 2. If 1 is true make a giant rows and columns (R&C) using concat as shown above + * Let all operators run amok on that R&C + * 3. If 1 is false + * Read a frame + * keep the older row in a class variable + * check row by row and compare current with older row to check if partition boundary is reached + * when frame partition by changes + * create R&C for those particular set of columns, they would have the same partition key + * output will be a single R&C + * write to output channel + * + * + * Future thoughts: {@link https://github.com/apache/druid/issues/16126} + * + * 1. We are writing 1 partition to each frame in this way. In case of low cardinality data + * we will me making a large number of small frames. We can have a check to keep size of frame to a value + * say 20k rows and keep on adding to the same pending frame and not create a new frame + * + * 2. Current approach with R&C and operators materialize a single R&C for processing. In case of data + * with high cardinality a single R&C might be too big to consume. Same for the case of empty OVER() clause + * Most of the window operations like SUM(), RANK(), RANGE() etc. can be made with 2 passes of the data. + * We might think to reimplement them in the MSQ way so that we do not have to materialize so much data + */ + + // Phase 1 of the execution + // eagerly validate presence of empty OVER() clause + if (isOverEmpty) { + // if OVER() found + // have to bring all data to a single executor for processing + // convert each frame to rac + // concat all the racs to make a giant rac + // let all operators run on the giant rac when channel is finished + if (inputChannel.canRead()) { + final Frame frame = inputChannel.read(); + convertRowFrameToRowsAndColumns(frame); + } else if (inputChannel.isFinished()) { + runAllOpsOnMultipleRac(frameRowsAndCols); + return ReturnOrAwait.returnObject(Unit.instance()); + } else { + return ReturnOrAwait.awaitAll(inputChannels().size()); + } + return ReturnOrAwait.runAgain(); + } else { + // Aha, you found a PARTITION BY and maybe ORDER BY TO + // PARTITION BY can also be on multiple keys + // typically the last stage would already partition and sort for you + // figure out frame boundaries and convert each distinct group to a rac + // then run the windowing operator only on each rac + if (frameCursor == null || frameCursor.isDone()) { + if (readableInputs.isEmpty()) { + return ReturnOrAwait.awaitAll(1); + } else if (inputChannel.canRead()) { + final Frame frame = inputChannel.read(); + frameCursor = FrameProcessors.makeCursor(frame, frameReader); + final ColumnSelectorFactory frameColumnSelectorFactory = frameCursor.getColumnSelectorFactory(); + partitionColsIndex = findPartitionColumns(frameReader.signature()); + final Supplier<Object>[] fieldSuppliers = new Supplier[frameReader.signature().size()]; + for (int i = 0; i < fieldSuppliers.length; i++) { + final ColumnValueSelector<?> selector = + frameColumnSelectorFactory.makeColumnValueSelector(frameReader.signature().getColumnName(i)); + fieldSuppliers[i] = selector::getObject; + + } + rowSupplierFromFrameCursor = () -> { + final ResultRow row = ResultRow.create(fieldSuppliers.length); + for (int i = 0; i < fieldSuppliers.length; i++) { + row.set(i, fieldSuppliers[i].get()); + } + return row; + }; + } else if (inputChannel.isFinished()) { + // reaached end of channel + // if there is data remaining + // write it into a rac + // and run operators on it + if (!objectsOfASingleRac.isEmpty()) { + if (objectsOfASingleRac.size() > maxRowsMaterialized) { Review Comment: Added the guardrail -- This is an automated message from the Apache Git Service. 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