Examples with AbstractMapJoinOperator org.apache.hadoop.hive.ql.exec.AbstractMapJoinOperator used on opensource projects

Example 1 with AbstractMapJoinOperator

use of org.apache.hadoop.hive.ql.exec.AbstractMapJoinOperator in project hive by apache.

the class MapJoinProcessor method transform.

/**
   * Transform the query tree. For each join, check if it is a map-side join (user specified). If
   * yes, convert it to a map-side join.
   *
   * @param pactx
   *          current parse context
   */
@Override
public ParseContext transform(ParseContext pactx) throws SemanticException {
    List<MapJoinOperator> listMapJoinOps = new ArrayList<MapJoinOperator>();
    // traverse all the joins and convert them if necessary
    if (pactx.getJoinOps() != null) {
        Set<JoinOperator> joinMap = new HashSet<JoinOperator>();
        Set<MapJoinOperator> mapJoinMap = pactx.getMapJoinOps();
        if (mapJoinMap == null) {
            mapJoinMap = new HashSet<MapJoinOperator>();
            pactx.setMapJoinOps(mapJoinMap);
        }
        Iterator<JoinOperator> joinCtxIter = pactx.getJoinOps().iterator();
        while (joinCtxIter.hasNext()) {
            JoinOperator joinOp = joinCtxIter.next();
            int mapJoinPos = mapSideJoin(joinOp);
            if (mapJoinPos >= 0) {
                MapJoinOperator mapJoinOp = generateMapJoinOperator(pactx, joinOp, mapJoinPos);
                listMapJoinOps.add(mapJoinOp);
                mapJoinOp.getConf().setQBJoinTreeProps(joinOp.getConf());
                mapJoinMap.add(mapJoinOp);
            } else {
                joinOp.getConf().setQBJoinTreeProps(joinOp.getConf());
                joinMap.add(joinOp);
            }
        }
        // store the new joinContext
        pactx.setJoinOps(joinMap);
    }
    // Go over the list and find if a reducer is not needed
    List<AbstractMapJoinOperator<? extends MapJoinDesc>> listMapJoinOpsNoRed = new ArrayList<AbstractMapJoinOperator<? extends MapJoinDesc>>();
    // create a walker which walks the tree in a DFS manner while maintaining
    // the operator stack.
    // The dispatcher generates the plan from the operator tree
    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R0", MapJoinOperator.getOperatorName() + "%"), getCurrentMapJoin());
    opRules.put(new RuleRegExp("R1", MapJoinOperator.getOperatorName() + "%.*" + FileSinkOperator.getOperatorName() + "%"), getMapJoinFS());
    opRules.put(new RuleRegExp("R2", MapJoinOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"), getMapJoinDefault());
    opRules.put(new RuleRegExp("R4", MapJoinOperator.getOperatorName() + "%.*" + UnionOperator.getOperatorName() + "%"), getMapJoinDefault());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefault(), opRules, new MapJoinWalkerCtx(listMapJoinOpsNoRed, pactx));
    GraphWalker ogw = new GenMapRedWalker(disp);
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(listMapJoinOps);
    ogw.startWalking(topNodes, null);
    pactx.setListMapJoinOpsNoReducer(listMapJoinOpsNoRed);
    return pactx;
}