Package org.apache.hadoop.hive.ql.optimizer

Source Code of org.apache.hadoop.hive.ql.optimizer.ReduceSinkMapJoinProc

/**
* 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.hadoop.hive.ql.optimizer;

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Stack;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.hive.ql.exec.FileSinkOperator;
import org.apache.hadoop.hive.ql.exec.HashTableDummyOperator;
import org.apache.hadoop.hive.ql.exec.MapJoinOperator;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.OperatorFactory;
import org.apache.hadoop.hive.ql.exec.ReduceSinkOperator;
import org.apache.hadoop.hive.ql.exec.RowSchema;
import org.apache.hadoop.hive.ql.lib.Node;
import org.apache.hadoop.hive.ql.lib.NodeProcessor;
import org.apache.hadoop.hive.ql.lib.NodeProcessorCtx;
import org.apache.hadoop.hive.ql.parse.GenTezProcContext;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.BaseWork;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.plan.HashTableDummyDesc;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
import org.apache.hadoop.hive.ql.plan.PlanUtils;
import org.apache.hadoop.hive.ql.plan.ReduceSinkDesc;
import org.apache.hadoop.hive.ql.plan.TableDesc;
import org.apache.hadoop.hive.ql.plan.TezEdgeProperty;
import org.apache.hadoop.hive.ql.plan.TezEdgeProperty.EdgeType;
import org.apache.hadoop.hive.ql.plan.TezWork;

public class ReduceSinkMapJoinProc implements NodeProcessor {

  protected transient Log LOG = LogFactory.getLog(this.getClass().getName());

  /* (non-Javadoc)
   * This processor addresses the RS-MJ case that occurs in tez on the small/hash
   * table side of things. The work that RS will be a part of must be connected
   * to the MJ work via be a broadcast edge.
   * We should not walk down the tree when we encounter this pattern because:
   * the type of work (map work or reduce work) needs to be determined
   * on the basis of the big table side because it may be a mapwork (no need for shuffle)
   * or reduce work.
   */
  @Override
  public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procContext, Object... nodeOutputs)
      throws SemanticException {
    GenTezProcContext context = (GenTezProcContext) procContext;
    MapJoinOperator mapJoinOp = (MapJoinOperator)nd;

    if (stack.size() < 2 || !(stack.get(stack.size() - 2) instanceof ReduceSinkOperator)) {
      context.currentMapJoinOperators.add(mapJoinOp);
      return null;
    }

    context.preceedingWork = null;
    context.currentRootOperator = null;

    ReduceSinkOperator parentRS = (ReduceSinkOperator)stack.get(stack.size() - 2);

    // remember the original parent list before we start modifying it.
    if (!context.mapJoinParentMap.containsKey(mapJoinOp)) {
      List<Operator<?>> parents = new ArrayList(mapJoinOp.getParentOperators());
      context.mapJoinParentMap.put(mapJoinOp, parents);
    }

    List<BaseWork> mapJoinWork = null;

    /*
     *  if there was a pre-existing work generated for the big-table mapjoin side,
     *  we need to hook the work generated for the RS (associated with the RS-MJ pattern)
     *  with the pre-existing work.
     *
     *  Otherwise, we need to associate that the mapjoin op
     *  to be linked to the RS work (associated with the RS-MJ pattern).
     *
     */
    mapJoinWork = context.mapJoinWorkMap.get(mapJoinOp);
    BaseWork parentWork;
    if (context.unionWorkMap.containsKey(parentRS)) {
      parentWork = context.unionWorkMap.get(parentRS);
    } else {
      assert context.childToWorkMap.get(parentRS).size() == 1;
      parentWork = context.childToWorkMap.get(parentRS).get(0);
    }

    // set the link between mapjoin and parent vertex
    int pos = context.mapJoinParentMap.get(mapJoinOp).indexOf(parentRS);
    if (pos == -1) {
      throw new SemanticException("Cannot find position of parent in mapjoin");
    }
    LOG.debug("Mapjoin "+mapJoinOp+", pos: "+pos+" --> "+parentWork.getName());
    mapJoinOp.getConf().getParentToInput().put(pos, parentWork.getName());

    int numBuckets = -1;
    EdgeType edgeType = EdgeType.BROADCAST_EDGE;
    if (mapJoinOp.getConf().isBucketMapJoin()) {
      numBuckets = (Integer) mapJoinOp.getConf().getBigTableBucketNumMapping().values().toArray()[0];
      if (mapJoinOp.getConf().getCustomBucketMapJoin()) {
        edgeType = EdgeType.CUSTOM_EDGE;
      } else {
        edgeType = EdgeType.CUSTOM_SIMPLE_EDGE;
      }
    }
    TezEdgeProperty edgeProp = new TezEdgeProperty(null, edgeType, numBuckets);

    if (mapJoinWork != null) {
      for (BaseWork myWork: mapJoinWork) {
        // link the work with the work associated with the reduce sink that triggered this rule
        TezWork tezWork = context.currentTask.getWork();
        LOG.debug("connecting "+parentWork.getName()+" with "+myWork.getName());
        tezWork.connect(parentWork, myWork, edgeProp);
       
        ReduceSinkOperator r = null;
        if (parentRS.getConf().getOutputName() != null) {
          LOG.debug("Cloning reduce sink for multi-child broadcast edge");
          // we've already set this one up. Need to clone for the next work.
          r = (ReduceSinkOperator) OperatorFactory.getAndMakeChild(
              (ReduceSinkDesc) parentRS.getConf().clone(), parentRS.getParentOperators());
          context.clonedReduceSinks.add(r);
        } else {
          r = parentRS;
        }
        // remember the output name of the reduce sink
        r.getConf().setOutputName(myWork.getName());
        context.connectedReduceSinks.add(r);
      }
    }

    // remember in case we need to connect additional work later
    Map<BaseWork, TezEdgeProperty> linkWorkMap = null;
    if (context.linkOpWithWorkMap.containsKey(mapJoinOp)) {
      linkWorkMap = context.linkOpWithWorkMap.get(mapJoinOp);
    } else {
      linkWorkMap = new HashMap<BaseWork, TezEdgeProperty>();
    }
    linkWorkMap.put(parentWork, edgeProp);
    context.linkOpWithWorkMap.put(mapJoinOp, linkWorkMap);
   
    List<ReduceSinkOperator> reduceSinks
      = context.linkWorkWithReduceSinkMap.get(parentWork);
    if (reduceSinks == null) {
      reduceSinks = new ArrayList<ReduceSinkOperator>();
    }
    reduceSinks.add(parentRS);
    context.linkWorkWithReduceSinkMap.put(parentWork, reduceSinks);

    // create the dummy operators
    List<Operator<? extends OperatorDesc>> dummyOperators =
        new ArrayList<Operator<? extends OperatorDesc>>();

    // create an new operator: HashTableDummyOperator, which share the table desc
    HashTableDummyDesc desc = new HashTableDummyDesc();
    @SuppressWarnings("unchecked")
    HashTableDummyOperator dummyOp = (HashTableDummyOperator) OperatorFactory.get(desc);
    TableDesc tbl;

    // need to create the correct table descriptor for key/value
    RowSchema rowSchema = parentRS.getParentOperators().get(0).getSchema();
    tbl = PlanUtils.getReduceValueTableDesc(PlanUtils.getFieldSchemasFromRowSchema(rowSchema, ""));
    dummyOp.getConf().setTbl(tbl);

    Map<Byte, List<ExprNodeDesc>> keyExprMap = mapJoinOp.getConf().getKeys();
    List<ExprNodeDesc> keyCols = keyExprMap.get(Byte.valueOf((byte) 0));
    StringBuffer keyOrder = new StringBuffer();
    for (ExprNodeDesc k: keyCols) {
      keyOrder.append("+");
    }
    TableDesc keyTableDesc = PlanUtils.getReduceKeyTableDesc(PlanUtils
        .getFieldSchemasFromColumnList(keyCols, "mapjoinkey"), keyOrder.toString());
    mapJoinOp.getConf().setKeyTableDesc(keyTableDesc);

    // let the dummy op be the parent of mapjoin op
    mapJoinOp.replaceParent(parentRS, dummyOp);
    List<Operator<? extends OperatorDesc>> dummyChildren =
      new ArrayList<Operator<? extends OperatorDesc>>();
    dummyChildren.add(mapJoinOp);
    dummyOp.setChildOperators(dummyChildren);
    dummyOperators.add(dummyOp);

    // cut the operator tree so as to not retain connections from the parent RS downstream
    List<Operator<? extends OperatorDesc>> childOperators = parentRS.getChildOperators();
    int childIndex = childOperators.indexOf(mapJoinOp);
    childOperators.remove(childIndex);

    // the "work" needs to know about the dummy operators. They have to be separately initialized
    // at task startup
    if (mapJoinWork != null) {
      for (BaseWork myWork: mapJoinWork) {
        myWork.addDummyOp(dummyOp);
      }
    }
    if (context.linkChildOpWithDummyOp.containsKey(mapJoinOp)) {
      for (Operator<?> op: context.linkChildOpWithDummyOp.get(mapJoinOp)) {
        dummyOperators.add(op);
      }
    }
    context.linkChildOpWithDummyOp.put(mapJoinOp, dummyOperators);

    return true;
  }
}
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