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From: twalthr <git@git.apache.org>
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Subject: [GitHub] flink pull request #2938: [FLINK-4692] [tableApi] Add tumbling group-windows...
Content-Type: text/plain
Message-Id: <20170111105708.1D081DFB79@git1-us-west.apache.org>
Date: Wed, 11 Jan 2017 10:57:08 +0000 (UTC)
archived-at: Wed, 11 Jan 2017 10:58:14 -0000

Github user twalthr commented on a diff in the pull request:

    https://github.com/apache/flink/pull/2938#discussion_r95549888
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/dataset/DataSetWindowAggregate.scala ---
    @@ -0,0 +1,244 @@
    +/*
    + * 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.flink.table.plan.nodes.dataset
    +
    +import org.apache.calcite.plan.{RelOptCluster, RelOptCost, RelOptPlanner, RelTraitSet}
    +import org.apache.calcite.rel.`type`.RelDataType
    +import org.apache.calcite.rel.core.AggregateCall
    +import org.apache.calcite.rel.metadata.RelMetadataQuery
    +import org.apache.calcite.rel.{RelNode, RelWriter, SingleRel}
    +import org.apache.flink.api.common.operators.Order
    +import org.apache.flink.api.common.typeinfo.TypeInformation
    +import org.apache.flink.api.java.DataSet
    +import org.apache.flink.api.java.typeutils.{ResultTypeQueryable, RowTypeInfo}
    +import org.apache.flink.table.api.BatchTableEnvironment
    +import org.apache.flink.table.calcite.FlinkRelBuilder.NamedWindowProperty
    +import org.apache.flink.table.calcite.FlinkTypeFactory
    +import org.apache.flink.table.plan.logical._
    +import org.apache.flink.table.plan.nodes.FlinkAggregate
    +import org.apache.flink.table.runtime.aggregate.AggregateUtil.{CalcitePair, _}
    +import org.apache.flink.table.typeutils.TypeCheckUtils.isTimeInterval
    +import org.apache.flink.table.typeutils.TypeConverter
    +import org.apache.flink.types.Row
    +
    +import scala.collection.JavaConversions._
    +
    +/**
    +  * Flink RelNode which matches along with a LogicalWindowAggregate.
    +  */
    +class DataSetWindowAggregate(
    +    window: LogicalWindow,
    +    namedProperties: Seq[NamedWindowProperty],
    +    cluster: RelOptCluster,
    +    traitSet: RelTraitSet,
    +    inputNode: RelNode,
    +    namedAggregates: Seq[CalcitePair[AggregateCall, String]],
    +    rowRelDataType: RelDataType,
    +    inputType: RelDataType,
    +    grouping: Array[Int])
    +  extends SingleRel(cluster, traitSet, inputNode)
    +  with FlinkAggregate
    +  with DataSetRel {
    +
    +  override def deriveRowType() = rowRelDataType
    +
    +  override def copy(traitSet: RelTraitSet, inputs: java.util.List[RelNode]): RelNode = {
    +    new DataSetWindowAggregate(
    +      window,
    +      namedProperties,
    +      cluster,
    +      traitSet,
    +      inputs.get(0),
    +      namedAggregates,
    +      getRowType,
    +      inputType,
    +      grouping)
    +  }
    +
    +  override def toString: String = {
    +    s"Aggregate(${
    +      if (!grouping.isEmpty) {
    +        s"groupBy: (${groupingToString(inputType, grouping)}), "
    +      } else {
    +        ""
    +      }
    +    }window: ($window), " +
    +      s"select: (${
    +        aggregationToString(
    +          inputType,
    +          grouping,
    +          getRowType,
    +          namedAggregates,
    +          namedProperties)
    +      }))"
    +  }
    +
    +  override def explainTerms(pw: RelWriter): RelWriter = {
    +    super.explainTerms(pw)
    +      .itemIf("groupBy", groupingToString(inputType, grouping), !grouping.isEmpty)
    +      .item("window", window)
    +      .item(
    +        "select", aggregationToString(
    +          inputType,
    +          grouping,
    +          getRowType,
    +          namedAggregates,
    +          namedProperties))
    +  }
    +
    +  override def computeSelfCost (planner: RelOptPlanner, metadata: RelMetadataQuery): RelOptCost = {
    +    val child = this.getInput
    +    val rowCnt = metadata.getRowCount(child)
    +    val rowSize = this.estimateRowSize(child.getRowType)
    +    val aggCnt = this.namedAggregates.size
    +    planner.getCostFactory.makeCost(rowCnt, rowCnt * aggCnt, rowCnt * rowSize)
    +  }
    +
    +  override def translateToPlan(
    +    tableEnv: BatchTableEnvironment,
    +    expectedType: Option[TypeInformation[Any]]): DataSet[Any] = {
    +
    +    val config = tableEnv.getConfig
    +
    +    val inputDS = getInput.asInstanceOf[DataSetRel].translateToPlan(
    +      tableEnv,
    +      // tell the input operator that this operator currently only supports Rows as input
    +      Some(TypeConverter.DEFAULT_ROW_TYPE))
    +
    +    val result = window match {
    +      case EventTimeTumblingGroupWindow(_, _, size) =>
    +        createEventTimeTumblingWindowDataSet(inputDS, isTimeInterval(size.resultType))
    +      case EventTimeSessionGroupWindow(_, _, _) =>
    +        throw new UnsupportedOperationException(
    +          "Event-time session windows on batch are currently not supported")
    +      case EventTimeSlidingGroupWindow(_, _, _, _) =>
    +        throw new UnsupportedOperationException(
    +          "Event-time sliding windows on batch are currently not supported")
    +      case _: ProcessingTimeGroupWindow =>
    +        throw new UnsupportedOperationException(
    +          "Processing-time tumbling windows are not supported on batch tables, " +
    +            "window on batch must declare a time attribute over which the query is evaluated.")
    +    }
    +
    +    // if the expected type is not a Row, inject a mapper to convert to the expected type
    +    expectedType match {
    +      case Some(typeInfo) if typeInfo.getTypeClass != classOf[Row] =>
    +        val mapName = s"convert: (${getRowType.getFieldNames.toList.mkString(", ")})"
    +        result.map(
    +          getConversionMapper(
    +            config = config,
    +            nullableInput = false,
    +            inputType = resultRowTypeInfo.asInstanceOf[TypeInformation[Any]],
    +            expectedType = expectedType.get,
    +            conversionOperatorName = "DataSetWindowAggregateConversion",
    +            fieldNames = getRowType.getFieldNames
    +          ))
    +          .name(mapName)
    +      case _ => result
    +    }
    +  }
    +
    +
    +  private def createEventTimeTumblingWindowDataSet(
    +      inputDS: DataSet[Any],
    +      isTimeWindow: Boolean)
    +    : DataSet[Any] = {
    +    val mapFunction = createDataSetWindowPrepareMapFunction(
    +      window,
    +      namedAggregates,
    +      grouping,
    +      inputType)
    +    val groupReduceFunction = createDataSetWindowAggGroupReduceFunction(
    +      window,
    +      namedAggregates,
    +      inputType,
    +      getRowType,
    +      grouping,
    +      namedProperties)
    +
    +    val mappedInput = inputDS
    +      .map(mapFunction)
    +      .name(prepareOperatorName)
    +
    +    if (isTimeWindow) {
    +      // grouped time window aggregation
    +      val mapReturnType = mapFunction.asInstanceOf[ResultTypeQueryable[Row]].getProducedType
    +      // group by grouping keys and rowtime field (the last field in the row)
    +      val groupingKeys = grouping.indices ++ Seq(mapReturnType.getArity - 1)
    +      mappedInput.asInstanceOf[DataSet[Row]]
    +        .groupBy(groupingKeys: _*)
    +        .reduceGroup(groupReduceFunction)
    +        .returns(resultRowTypeInfo)
    +        .name(aggregateOperatorName)
    +        .asInstanceOf[DataSet[Any]]
    +    } else {
    +      // count window
    +      val groupingKeys = grouping.indices.toArray
    +      if (groupingKeys.length > 0) {
    +        // grouped aggregation
    +        mappedInput.asInstanceOf[DataSet[Row]]
    +          .groupBy(groupingKeys: _*)
    +          // sort on time field, it's the one after grouping keys
    +          .sortGroup(groupingKeys.length, Order.ASCENDING)
    --- End diff --
    
    Shouldn't this be `mapReturnType.getArity - 1`? According to the docs of `AggregateUtil#createDataSetWindowPrepareMapFunction` the time field should be at the end?


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