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Example 1 with ConditionalWork

use of org.apache.hadoop.hive.ql.plan.ConditionalWork in project hive by apache.

the class GenMRSkewJoinProcessor method processSkewJoin.

/**
   * Create tasks for processing skew joins. The idea is (HIVE-964) to use
   * separated jobs and map-joins to handle skew joins.
   * <p>
   * <ul>
   * <li>
   * Number of mr jobs to handle skew keys is the number of table minus 1 (we
   * can stream the last table, so big keys in the last table will not be a
   * problem).
   * <li>
   * At runtime in Join, we output big keys in one table into one corresponding
   * directories, and all same keys in other tables into different dirs(one for
   * each table). The directories will look like:
   * <ul>
   * <li>
   * dir-T1-bigkeys(containing big keys in T1), dir-T2-keys(containing keys
   * which is big in T1),dir-T3-keys(containing keys which is big in T1), ...
   * <li>
   * dir-T1-keys(containing keys which is big in T2), dir-T2-bigkeys(containing
   * big keys in T2),dir-T3-keys(containing keys which is big in T2), ...
   * <li>
   * dir-T1-keys(containing keys which is big in T3), dir-T2-keys(containing big
   * keys in T3),dir-T3-bigkeys(containing keys which is big in T3), ... .....
   * </ul>
   * </ul>
   * For each table, we launch one mapjoin job, taking the directory containing
   * big keys in this table and corresponding dirs in other tables as input.
   * (Actally one job for one row in the above.)
   *
   * <p>
   * For more discussions, please check
   * https://issues.apache.org/jira/browse/HIVE-964.
   *
   */
@SuppressWarnings("unchecked")
public static void processSkewJoin(JoinOperator joinOp, Task<? extends Serializable> currTask, ParseContext parseCtx) throws SemanticException {
    // now does not work with outer joins
    if (!GenMRSkewJoinProcessor.skewJoinEnabled(parseCtx.getConf(), joinOp)) {
        return;
    }
    List<Task<? extends Serializable>> children = currTask.getChildTasks();
    Path baseTmpDir = parseCtx.getContext().getMRTmpPath();
    JoinDesc joinDescriptor = joinOp.getConf();
    Map<Byte, List<ExprNodeDesc>> joinValues = joinDescriptor.getExprs();
    int numAliases = joinValues.size();
    Map<Byte, Path> bigKeysDirMap = new HashMap<Byte, Path>();
    Map<Byte, Map<Byte, Path>> smallKeysDirMap = new HashMap<Byte, Map<Byte, Path>>();
    Map<Byte, Path> skewJoinJobResultsDir = new HashMap<Byte, Path>();
    Byte[] tags = joinDescriptor.getTagOrder();
    for (int i = 0; i < numAliases; i++) {
        Byte alias = tags[i];
        bigKeysDirMap.put(alias, getBigKeysDir(baseTmpDir, alias));
        Map<Byte, Path> smallKeysMap = new HashMap<Byte, Path>();
        smallKeysDirMap.put(alias, smallKeysMap);
        for (Byte src2 : tags) {
            if (!src2.equals(alias)) {
                smallKeysMap.put(src2, getSmallKeysDir(baseTmpDir, alias, src2));
            }
        }
        skewJoinJobResultsDir.put(alias, getBigKeysSkewJoinResultDir(baseTmpDir, alias));
    }
    joinDescriptor.setHandleSkewJoin(true);
    joinDescriptor.setBigKeysDirMap(bigKeysDirMap);
    joinDescriptor.setSmallKeysDirMap(smallKeysDirMap);
    joinDescriptor.setSkewKeyDefinition(HiveConf.getIntVar(parseCtx.getConf(), HiveConf.ConfVars.HIVESKEWJOINKEY));
    HashMap<Path, Task<? extends Serializable>> bigKeysDirToTaskMap = new HashMap<Path, Task<? extends Serializable>>();
    List<Serializable> listWorks = new ArrayList<Serializable>();
    List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
    MapredWork currPlan = (MapredWork) currTask.getWork();
    TableDesc keyTblDesc = (TableDesc) currPlan.getReduceWork().getKeyDesc().clone();
    List<String> joinKeys = Utilities.getColumnNames(keyTblDesc.getProperties());
    List<String> joinKeyTypes = Utilities.getColumnTypes(keyTblDesc.getProperties());
    Map<Byte, TableDesc> tableDescList = new HashMap<Byte, TableDesc>();
    Map<Byte, RowSchema> rowSchemaList = new HashMap<Byte, RowSchema>();
    Map<Byte, List<ExprNodeDesc>> newJoinValues = new HashMap<Byte, List<ExprNodeDesc>>();
    Map<Byte, List<ExprNodeDesc>> newJoinKeys = new HashMap<Byte, List<ExprNodeDesc>>();
    // used for create mapJoinDesc, should be in order
    List<TableDesc> newJoinValueTblDesc = new ArrayList<TableDesc>();
    for (Byte tag : tags) {
        newJoinValueTblDesc.add(null);
    }
    for (int i = 0; i < numAliases; i++) {
        Byte alias = tags[i];
        List<ExprNodeDesc> valueCols = joinValues.get(alias);
        String colNames = "";
        String colTypes = "";
        int columnSize = valueCols.size();
        List<ExprNodeDesc> newValueExpr = new ArrayList<ExprNodeDesc>();
        List<ExprNodeDesc> newKeyExpr = new ArrayList<ExprNodeDesc>();
        ArrayList<ColumnInfo> columnInfos = new ArrayList<ColumnInfo>();
        boolean first = true;
        for (int k = 0; k < columnSize; k++) {
            TypeInfo type = valueCols.get(k).getTypeInfo();
            // any name, it does not matter.
            String newColName = i + "_VALUE_" + k;
            ColumnInfo columnInfo = new ColumnInfo(newColName, type, alias.toString(), false);
            columnInfos.add(columnInfo);
            newValueExpr.add(new ExprNodeColumnDesc(columnInfo));
            if (!first) {
                colNames = colNames + ",";
                colTypes = colTypes + ",";
            }
            first = false;
            colNames = colNames + newColName;
            colTypes = colTypes + valueCols.get(k).getTypeString();
        }
        // we are putting join keys at last part of the spilled table
        for (int k = 0; k < joinKeys.size(); k++) {
            if (!first) {
                colNames = colNames + ",";
                colTypes = colTypes + ",";
            }
            first = false;
            colNames = colNames + joinKeys.get(k);
            colTypes = colTypes + joinKeyTypes.get(k);
            ColumnInfo columnInfo = new ColumnInfo(joinKeys.get(k), TypeInfoFactory.getPrimitiveTypeInfo(joinKeyTypes.get(k)), alias.toString(), false);
            columnInfos.add(columnInfo);
            newKeyExpr.add(new ExprNodeColumnDesc(columnInfo));
        }
        newJoinValues.put(alias, newValueExpr);
        newJoinKeys.put(alias, newKeyExpr);
        tableDescList.put(alias, Utilities.getTableDesc(colNames, colTypes));
        rowSchemaList.put(alias, new RowSchema(columnInfos));
        // construct value table Desc
        String valueColNames = "";
        String valueColTypes = "";
        first = true;
        for (int k = 0; k < columnSize; k++) {
            // any name, it does not matter.
            String newColName = i + "_VALUE_" + k;
            if (!first) {
                valueColNames = valueColNames + ",";
                valueColTypes = valueColTypes + ",";
            }
            valueColNames = valueColNames + newColName;
            valueColTypes = valueColTypes + valueCols.get(k).getTypeString();
            first = false;
        }
        newJoinValueTblDesc.set(Byte.valueOf((byte) i), Utilities.getTableDesc(valueColNames, valueColTypes));
    }
    joinDescriptor.setSkewKeysValuesTables(tableDescList);
    joinDescriptor.setKeyTableDesc(keyTblDesc);
    for (int i = 0; i < numAliases - 1; i++) {
        Byte src = tags[i];
        MapWork newPlan = PlanUtils.getMapRedWork().getMapWork();
        // This code has been only added for testing
        boolean mapperCannotSpanPartns = parseCtx.getConf().getBoolVar(HiveConf.ConfVars.HIVE_MAPPER_CANNOT_SPAN_MULTIPLE_PARTITIONS);
        newPlan.setMapperCannotSpanPartns(mapperCannotSpanPartns);
        MapredWork clonePlan = SerializationUtilities.clonePlan(currPlan);
        Operator<? extends OperatorDesc>[] parentOps = new TableScanOperator[tags.length];
        for (int k = 0; k < tags.length; k++) {
            Operator<? extends OperatorDesc> ts = GenMapRedUtils.createTemporaryTableScanOperator(joinOp.getCompilationOpContext(), rowSchemaList.get((byte) k));
            ((TableScanOperator) ts).setTableDesc(tableDescList.get((byte) k));
            parentOps[k] = ts;
        }
        Operator<? extends OperatorDesc> tblScan_op = parentOps[i];
        ArrayList<String> aliases = new ArrayList<String>();
        String alias = src.toString().intern();
        aliases.add(alias);
        Path bigKeyDirPath = bigKeysDirMap.get(src);
        newPlan.addPathToAlias(bigKeyDirPath, aliases);
        newPlan.getAliasToWork().put(alias, tblScan_op);
        PartitionDesc part = new PartitionDesc(tableDescList.get(src), null);
        newPlan.addPathToPartitionInfo(bigKeyDirPath, part);
        newPlan.getAliasToPartnInfo().put(alias, part);
        Operator<? extends OperatorDesc> reducer = clonePlan.getReduceWork().getReducer();
        assert reducer instanceof JoinOperator;
        JoinOperator cloneJoinOp = (JoinOperator) reducer;
        String dumpFilePrefix = "mapfile" + PlanUtils.getCountForMapJoinDumpFilePrefix();
        MapJoinDesc mapJoinDescriptor = new MapJoinDesc(newJoinKeys, keyTblDesc, newJoinValues, newJoinValueTblDesc, newJoinValueTblDesc, joinDescriptor.getOutputColumnNames(), i, joinDescriptor.getConds(), joinDescriptor.getFilters(), joinDescriptor.getNoOuterJoin(), dumpFilePrefix);
        mapJoinDescriptor.setTagOrder(tags);
        mapJoinDescriptor.setHandleSkewJoin(false);
        mapJoinDescriptor.setNullSafes(joinDescriptor.getNullSafes());
        MapredLocalWork localPlan = new MapredLocalWork(new LinkedHashMap<String, Operator<? extends OperatorDesc>>(), new LinkedHashMap<String, FetchWork>());
        Map<Byte, Path> smallTblDirs = smallKeysDirMap.get(src);
        for (int j = 0; j < numAliases; j++) {
            if (j == i) {
                continue;
            }
            Byte small_alias = tags[j];
            Operator<? extends OperatorDesc> tblScan_op2 = parentOps[j];
            localPlan.getAliasToWork().put(small_alias.toString(), tblScan_op2);
            Path tblDir = smallTblDirs.get(small_alias);
            localPlan.getAliasToFetchWork().put(small_alias.toString(), new FetchWork(tblDir, tableDescList.get(small_alias)));
        }
        newPlan.setMapRedLocalWork(localPlan);
        // construct a map join and set it as the child operator of tblScan_op
        MapJoinOperator mapJoinOp = (MapJoinOperator) OperatorFactory.getAndMakeChild(joinOp.getCompilationOpContext(), mapJoinDescriptor, (RowSchema) null, parentOps);
        // change the children of the original join operator to point to the map
        // join operator
        List<Operator<? extends OperatorDesc>> childOps = cloneJoinOp.getChildOperators();
        for (Operator<? extends OperatorDesc> childOp : childOps) {
            childOp.replaceParent(cloneJoinOp, mapJoinOp);
        }
        mapJoinOp.setChildOperators(childOps);
        HiveConf jc = new HiveConf(parseCtx.getConf(), GenMRSkewJoinProcessor.class);
        newPlan.setNumMapTasks(HiveConf.getIntVar(jc, HiveConf.ConfVars.HIVESKEWJOINMAPJOINNUMMAPTASK));
        newPlan.setMinSplitSize(HiveConf.getLongVar(jc, HiveConf.ConfVars.HIVESKEWJOINMAPJOINMINSPLIT));
        newPlan.setInputformat(HiveInputFormat.class.getName());
        MapredWork w = new MapredWork();
        w.setMapWork(newPlan);
        Task<? extends Serializable> skewJoinMapJoinTask = TaskFactory.get(w, jc);
        skewJoinMapJoinTask.setFetchSource(currTask.isFetchSource());
        bigKeysDirToTaskMap.put(bigKeyDirPath, skewJoinMapJoinTask);
        listWorks.add(skewJoinMapJoinTask.getWork());
        listTasks.add(skewJoinMapJoinTask);
    }
    if (children != null) {
        for (Task<? extends Serializable> tsk : listTasks) {
            for (Task<? extends Serializable> oldChild : children) {
                tsk.addDependentTask(oldChild);
            }
        }
        currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
        for (Task<? extends Serializable> oldChild : children) {
            oldChild.getParentTasks().remove(currTask);
        }
        listTasks.addAll(children);
    }
    ConditionalResolverSkewJoinCtx context = new ConditionalResolverSkewJoinCtx(bigKeysDirToTaskMap, children);
    ConditionalWork cndWork = new ConditionalWork(listWorks);
    ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork, parseCtx.getConf());
    cndTsk.setListTasks(listTasks);
    cndTsk.setResolver(new ConditionalResolverSkewJoin());
    cndTsk.setResolverCtx(context);
    currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
    currTask.addDependentTask(cndTsk);
    return;
}
Also used : MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) Task(org.apache.hadoop.hive.ql.exec.Task) Serializable(java.io.Serializable) TableScanOperator(org.apache.hadoop.hive.ql.exec.TableScanOperator) HashMap(java.util.HashMap) LinkedHashMap(java.util.LinkedHashMap) ArrayList(java.util.ArrayList) ConditionalWork(org.apache.hadoop.hive.ql.plan.ConditionalWork) ColumnInfo(org.apache.hadoop.hive.ql.exec.ColumnInfo) MapredWork(org.apache.hadoop.hive.ql.plan.MapredWork) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) ArrayList(java.util.ArrayList) List(java.util.List) HiveConf(org.apache.hadoop.hive.conf.HiveConf) ExprNodeDesc(org.apache.hadoop.hive.ql.plan.ExprNodeDesc) ConditionalResolverSkewJoin(org.apache.hadoop.hive.ql.plan.ConditionalResolverSkewJoin) MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) RowSchema(org.apache.hadoop.hive.ql.exec.RowSchema) TypeInfo(org.apache.hadoop.hive.serde2.typeinfo.TypeInfo) MapredLocalWork(org.apache.hadoop.hive.ql.plan.MapredLocalWork) TableDesc(org.apache.hadoop.hive.ql.plan.TableDesc) MapJoinDesc(org.apache.hadoop.hive.ql.plan.MapJoinDesc) JoinDesc(org.apache.hadoop.hive.ql.plan.JoinDesc) HashMap(java.util.HashMap) LinkedHashMap(java.util.LinkedHashMap) Map(java.util.Map) OperatorDesc(org.apache.hadoop.hive.ql.plan.OperatorDesc) MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) TableScanOperator(org.apache.hadoop.hive.ql.exec.TableScanOperator) Operator(org.apache.hadoop.hive.ql.exec.Operator) HiveInputFormat(org.apache.hadoop.hive.ql.io.HiveInputFormat) ExprNodeColumnDesc(org.apache.hadoop.hive.ql.plan.ExprNodeColumnDesc) Path(org.apache.hadoop.fs.Path) MapJoinDesc(org.apache.hadoop.hive.ql.plan.MapJoinDesc) ConditionalResolverSkewJoinCtx(org.apache.hadoop.hive.ql.plan.ConditionalResolverSkewJoin.ConditionalResolverSkewJoinCtx) MapWork(org.apache.hadoop.hive.ql.plan.MapWork) FetchWork(org.apache.hadoop.hive.ql.plan.FetchWork) PartitionDesc(org.apache.hadoop.hive.ql.plan.PartitionDesc)

Example 2 with ConditionalWork

use of org.apache.hadoop.hive.ql.plan.ConditionalWork in project hive by apache.

the class SortMergeJoinTaskDispatcher method processCurrentTask.

@Override
public Task<? extends Serializable> processCurrentTask(MapRedTask currTask, ConditionalTask conditionalTask, Context context) throws SemanticException {
    // whether it contains a sort merge join operator
    MapredWork currWork = currTask.getWork();
    SMBMapJoinOperator originalSMBJoinOp = getSMBMapJoinOp(currWork);
    if (!isEligibleForOptimization(originalSMBJoinOp)) {
        return null;
    }
    currTask.setTaskTag(Task.CONVERTED_SORTMERGEJOIN);
    // get parseCtx for this Join Operator
    ParseContext parseCtx = physicalContext.getParseContext();
    // Convert the work containing to sort-merge join into a work, as if it had a regular join.
    // Note that the operator tree is not changed - is still contains the SMB join, but the
    // plan is changed (aliasToWork etc.) to contain all the paths as if it was a regular join.
    // This is used to convert the plan to a map-join, and then the original SMB join plan is used
    // as a backup task.
    MapredWork currJoinWork = convertSMBWorkToJoinWork(currWork, originalSMBJoinOp);
    SMBMapJoinOperator newSMBJoinOp = getSMBMapJoinOp(currJoinWork);
    currWork.getMapWork().setLeftInputJoin(originalSMBJoinOp.getConf().isLeftInputJoin());
    currWork.getMapWork().setBaseSrc(originalSMBJoinOp.getConf().getBaseSrc());
    currWork.getMapWork().setMapAliases(originalSMBJoinOp.getConf().getMapAliases());
    currJoinWork.getMapWork().setLeftInputJoin(originalSMBJoinOp.getConf().isLeftInputJoin());
    currJoinWork.getMapWork().setBaseSrc(originalSMBJoinOp.getConf().getBaseSrc());
    currJoinWork.getMapWork().setMapAliases(originalSMBJoinOp.getConf().getMapAliases());
    // create conditional work list and task list
    List<Serializable> listWorks = new ArrayList<Serializable>();
    List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
    // create task to aliases mapping and alias to input file mapping for resolver
    // Must be deterministic order map for consistent q-test output across Java versions
    HashMap<Task<? extends Serializable>, Set<String>> taskToAliases = new LinkedHashMap<Task<? extends Serializable>, Set<String>>();
    // Note that pathToAlias will behave as if the original plan was a join plan
    HashMap<Path, ArrayList<String>> pathToAliases = currJoinWork.getMapWork().getPathToAliases();
    // generate a map join task for the big table
    SMBJoinDesc originalSMBJoinDesc = originalSMBJoinOp.getConf();
    Byte[] order = originalSMBJoinDesc.getTagOrder();
    int numAliases = order.length;
    Set<Integer> bigTableCandidates = MapJoinProcessor.getBigTableCandidates(originalSMBJoinDesc.getConds());
    HashMap<String, Long> aliasToSize = new HashMap<String, Long>();
    Configuration conf = context.getConf();
    try {
        long aliasTotalKnownInputSize = getTotalKnownInputSize(context, currJoinWork.getMapWork(), pathToAliases, aliasToSize);
        long ThresholdOfSmallTblSizeSum = HiveConf.getLongVar(conf, HiveConf.ConfVars.HIVESMALLTABLESFILESIZE);
        for (int bigTablePosition = 0; bigTablePosition < numAliases; bigTablePosition++) {
            // this table cannot be big table
            if (!bigTableCandidates.contains(bigTablePosition)) {
                continue;
            }
            // create map join task for the given big table position
            MapRedTask newTask = convertSMBTaskToMapJoinTask(currJoinWork, bigTablePosition, newSMBJoinOp);
            MapWork mapWork = newTask.getWork().getMapWork();
            Operator<?> parentOp = originalSMBJoinOp.getParentOperators().get(bigTablePosition);
            Set<String> aliases = GenMapRedUtils.findAliases(mapWork, parentOp);
            long aliasKnownSize = Utilities.sumOf(aliasToSize, aliases);
            if (aliasKnownSize > 0) {
                long smallTblTotalKnownSize = aliasTotalKnownInputSize - aliasKnownSize;
                if (smallTblTotalKnownSize > ThresholdOfSmallTblSizeSum) {
                    // this table is not good to be a big table.
                    continue;
                }
            }
            // add into conditional task
            listWorks.add(newTask.getWork());
            listTasks.add(newTask);
            newTask.setTaskTag(Task.CONVERTED_MAPJOIN);
            newTask.setFetchSource(currTask.isFetchSource());
            // set up backup task
            newTask.setBackupTask(currTask);
            newTask.setBackupChildrenTasks(currTask.getChildTasks());
            // put the mapping task to aliases
            taskToAliases.put(newTask, aliases);
        }
    } catch (Exception e) {
        e.printStackTrace();
        throw new SemanticException("Generate Map Join Task Error: ", e);
    }
    // insert current common join task to conditional task
    listWorks.add(currTask.getWork());
    listTasks.add(currTask);
    // clear JoinTree and OP Parse Context
    currWork.getMapWork().setLeftInputJoin(false);
    currWork.getMapWork().setBaseSrc(null);
    currWork.getMapWork().setMapAliases(null);
    // create conditional task and insert conditional task into task tree
    ConditionalWork cndWork = new ConditionalWork(listWorks);
    ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork, parseCtx.getConf());
    cndTsk.setListTasks(listTasks);
    // set resolver and resolver context
    cndTsk.setResolver(new ConditionalResolverCommonJoin());
    ConditionalResolverCommonJoinCtx resolverCtx = new ConditionalResolverCommonJoinCtx();
    resolverCtx.setPathToAliases(pathToAliases);
    resolverCtx.setAliasToKnownSize(aliasToSize);
    resolverCtx.setTaskToAliases(taskToAliases);
    resolverCtx.setCommonJoinTask(currTask);
    resolverCtx.setLocalTmpDir(context.getLocalScratchDir(false));
    resolverCtx.setHdfsTmpDir(context.getMRScratchDir());
    cndTsk.setResolverCtx(resolverCtx);
    // replace the current task with the new generated conditional task
    replaceTaskWithConditionalTask(currTask, cndTsk);
    return cndTsk;
}
Also used : Serializable(java.io.Serializable) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) Task(org.apache.hadoop.hive.ql.exec.Task) MapRedTask(org.apache.hadoop.hive.ql.exec.mr.MapRedTask) Set(java.util.Set) SMBJoinDesc(org.apache.hadoop.hive.ql.plan.SMBJoinDesc) Configuration(org.apache.hadoop.conf.Configuration) HashMap(java.util.HashMap) LinkedHashMap(java.util.LinkedHashMap) ArrayList(java.util.ArrayList) ConditionalWork(org.apache.hadoop.hive.ql.plan.ConditionalWork) SMBMapJoinOperator(org.apache.hadoop.hive.ql.exec.SMBMapJoinOperator) LinkedHashMap(java.util.LinkedHashMap) MapRedTask(org.apache.hadoop.hive.ql.exec.mr.MapRedTask) ConditionalResolverCommonJoinCtx(org.apache.hadoop.hive.ql.plan.ConditionalResolverCommonJoin.ConditionalResolverCommonJoinCtx) MapredWork(org.apache.hadoop.hive.ql.plan.MapredWork) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) ConditionalResolverCommonJoin(org.apache.hadoop.hive.ql.plan.ConditionalResolverCommonJoin) SemanticException(org.apache.hadoop.hive.ql.parse.SemanticException) Path(org.apache.hadoop.fs.Path) SemanticException(org.apache.hadoop.hive.ql.parse.SemanticException) UnsupportedEncodingException(java.io.UnsupportedEncodingException) MapWork(org.apache.hadoop.hive.ql.plan.MapWork) ParseContext(org.apache.hadoop.hive.ql.parse.ParseContext)

Example 3 with ConditionalWork

use of org.apache.hadoop.hive.ql.plan.ConditionalWork in project hive by apache.

the class GenMapRedUtils method createCondTask.

/**
   * Construct a conditional task given the current leaf task, the MoveWork and the MapredWork.
   *
   * @param conf
   *          HiveConf
   * @param currTask
   *          current leaf task
   * @param dummyMoveWork
   *          MoveWork for the move task
   * @param mergeWork
   *          MapredWork for the merge task.
   * @param condInputPath
   *          the input directory of the merge/move task
   * @param condOutputPath
   *          the output directory of the merge/move task
   * @param moveTaskToLink
   *          a MoveTask that may be linked to the conditional sub-tasks
   * @param dependencyTask
   *          a dependency task that may be linked to the conditional sub-tasks
   * @return The conditional task
   */
private static ConditionalTask createCondTask(HiveConf conf, Task<? extends Serializable> currTask, MoveWork dummyMoveWork, Serializable mergeWork, Path condInputPath, Path condOutputPath, Task<MoveWork> moveTaskToLink, DependencyCollectionTask dependencyTask) {
    boolean shouldMergeMovePaths = (moveTaskToLink != null && dependencyTask == null && shouldMergeMovePaths(conf, condInputPath, condOutputPath, moveTaskToLink.getWork()));
    MoveWork workForMoveOnlyTask;
    if (shouldMergeMovePaths) {
        workForMoveOnlyTask = mergeMovePaths(condInputPath, moveTaskToLink.getWork());
    } else {
        workForMoveOnlyTask = dummyMoveWork;
    }
    // There are 3 options for this ConditionalTask:
    // 1) Merge the partitions
    // 2) Move the partitions (i.e. don't merge the partitions)
    // 3) Merge some partitions and move other partitions (i.e. merge some partitions and don't
    // merge others) in this case the merge is done first followed by the move to prevent
    // conflicts.
    Task<? extends Serializable> mergeOnlyMergeTask = TaskFactory.get(mergeWork, conf);
    Task<? extends Serializable> moveOnlyMoveTask = TaskFactory.get(workForMoveOnlyTask, conf);
    Task<? extends Serializable> mergeAndMoveMergeTask = TaskFactory.get(mergeWork, conf);
    Task<? extends Serializable> mergeAndMoveMoveTask = TaskFactory.get(dummyMoveWork, conf);
    // NOTE! It is necessary merge task is the parent of the move task, and not
    // the other way around, for the proper execution of the execute method of
    // ConditionalTask
    mergeAndMoveMergeTask.addDependentTask(mergeAndMoveMoveTask);
    List<Serializable> listWorks = new ArrayList<Serializable>();
    listWorks.add(workForMoveOnlyTask);
    listWorks.add(mergeWork);
    ConditionalWork cndWork = new ConditionalWork(listWorks);
    List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
    listTasks.add(moveOnlyMoveTask);
    listTasks.add(mergeOnlyMergeTask);
    listTasks.add(mergeAndMoveMergeTask);
    ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork, conf);
    cndTsk.setListTasks(listTasks);
    // create resolver
    cndTsk.setResolver(new ConditionalResolverMergeFiles());
    ConditionalResolverMergeFilesCtx mrCtx = new ConditionalResolverMergeFilesCtx(listTasks, condInputPath.toString());
    cndTsk.setResolverCtx(mrCtx);
    // make the conditional task as the child of the current leaf task
    currTask.addDependentTask(cndTsk);
    if (shouldMergeMovePaths) {
        // If a new MoveWork was created, then we should link all dependent tasks from the MoveWork to link.
        if (moveTaskToLink.getDependentTasks() != null) {
            for (Task dependentTask : moveTaskToLink.getDependentTasks()) {
                moveOnlyMoveTask.addDependentTask(dependentTask);
            }
        }
    } else {
        addDependentMoveTasks(moveTaskToLink, conf, moveOnlyMoveTask, dependencyTask);
    }
    addDependentMoveTasks(moveTaskToLink, conf, mergeOnlyMergeTask, dependencyTask);
    addDependentMoveTasks(moveTaskToLink, conf, mergeAndMoveMoveTask, dependencyTask);
    return cndTsk;
}
Also used : MoveWork(org.apache.hadoop.hive.ql.plan.MoveWork) ConditionalResolverMergeFiles(org.apache.hadoop.hive.ql.plan.ConditionalResolverMergeFiles) Serializable(java.io.Serializable) SparkTask(org.apache.hadoop.hive.ql.exec.spark.SparkTask) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) Task(org.apache.hadoop.hive.ql.exec.Task) MoveTask(org.apache.hadoop.hive.ql.exec.MoveTask) MapRedTask(org.apache.hadoop.hive.ql.exec.mr.MapRedTask) DependencyCollectionTask(org.apache.hadoop.hive.ql.exec.DependencyCollectionTask) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) ArrayList(java.util.ArrayList) ConditionalWork(org.apache.hadoop.hive.ql.plan.ConditionalWork) ConditionalResolverMergeFilesCtx(org.apache.hadoop.hive.ql.plan.ConditionalResolverMergeFiles.ConditionalResolverMergeFilesCtx)

Example 4 with ConditionalWork

use of org.apache.hadoop.hive.ql.plan.ConditionalWork in project hive by apache.

the class GenSparkSkewJoinProcessor method processSkewJoin.

@SuppressWarnings("unchecked")
public static void processSkewJoin(JoinOperator joinOp, Task<? extends Serializable> currTask, ReduceWork reduceWork, ParseContext parseCtx) throws SemanticException {
    SparkWork currentWork = ((SparkTask) currTask).getWork();
    if (currentWork.getChildren(reduceWork).size() > 0) {
        LOG.warn("Skip runtime skew join as the ReduceWork has child work and hasn't been split.");
        return;
    }
    List<Task<? extends Serializable>> children = currTask.getChildTasks();
    Path baseTmpDir = parseCtx.getContext().getMRTmpPath();
    JoinDesc joinDescriptor = joinOp.getConf();
    Map<Byte, List<ExprNodeDesc>> joinValues = joinDescriptor.getExprs();
    int numAliases = joinValues.size();
    Map<Byte, Path> bigKeysDirMap = new HashMap<Byte, Path>();
    Map<Byte, Map<Byte, Path>> smallKeysDirMap = new HashMap<Byte, Map<Byte, Path>>();
    Map<Byte, Path> skewJoinJobResultsDir = new HashMap<Byte, Path>();
    Byte[] tags = joinDescriptor.getTagOrder();
    // for each joining table, set dir for big key and small keys properly
    for (int i = 0; i < numAliases; i++) {
        Byte alias = tags[i];
        bigKeysDirMap.put(alias, GenMRSkewJoinProcessor.getBigKeysDir(baseTmpDir, alias));
        Map<Byte, Path> smallKeysMap = new HashMap<Byte, Path>();
        smallKeysDirMap.put(alias, smallKeysMap);
        for (Byte src2 : tags) {
            if (!src2.equals(alias)) {
                smallKeysMap.put(src2, GenMRSkewJoinProcessor.getSmallKeysDir(baseTmpDir, alias, src2));
            }
        }
        skewJoinJobResultsDir.put(alias, GenMRSkewJoinProcessor.getBigKeysSkewJoinResultDir(baseTmpDir, alias));
    }
    joinDescriptor.setHandleSkewJoin(true);
    joinDescriptor.setBigKeysDirMap(bigKeysDirMap);
    joinDescriptor.setSmallKeysDirMap(smallKeysDirMap);
    joinDescriptor.setSkewKeyDefinition(HiveConf.getIntVar(parseCtx.getConf(), HiveConf.ConfVars.HIVESKEWJOINKEY));
    // create proper table/column desc for spilled tables
    TableDesc keyTblDesc = (TableDesc) reduceWork.getKeyDesc().clone();
    List<String> joinKeys = Utilities.getColumnNames(keyTblDesc.getProperties());
    List<String> joinKeyTypes = Utilities.getColumnTypes(keyTblDesc.getProperties());
    Map<Byte, TableDesc> tableDescList = new HashMap<Byte, TableDesc>();
    Map<Byte, RowSchema> rowSchemaList = new HashMap<Byte, RowSchema>();
    Map<Byte, List<ExprNodeDesc>> newJoinValues = new HashMap<Byte, List<ExprNodeDesc>>();
    Map<Byte, List<ExprNodeDesc>> newJoinKeys = new HashMap<Byte, List<ExprNodeDesc>>();
    // used for create mapJoinDesc, should be in order
    List<TableDesc> newJoinValueTblDesc = new ArrayList<TableDesc>();
    for (int i = 0; i < tags.length; i++) {
        newJoinValueTblDesc.add(null);
    }
    for (int i = 0; i < numAliases; i++) {
        Byte alias = tags[i];
        List<ExprNodeDesc> valueCols = joinValues.get(alias);
        String colNames = "";
        String colTypes = "";
        int columnSize = valueCols.size();
        List<ExprNodeDesc> newValueExpr = new ArrayList<ExprNodeDesc>();
        List<ExprNodeDesc> newKeyExpr = new ArrayList<ExprNodeDesc>();
        ArrayList<ColumnInfo> columnInfos = new ArrayList<ColumnInfo>();
        boolean first = true;
        for (int k = 0; k < columnSize; k++) {
            TypeInfo type = valueCols.get(k).getTypeInfo();
            // any name, it does not matter.
            String newColName = i + "_VALUE_" + k;
            ColumnInfo columnInfo = new ColumnInfo(newColName, type, alias.toString(), false);
            columnInfos.add(columnInfo);
            newValueExpr.add(new ExprNodeColumnDesc(columnInfo.getType(), columnInfo.getInternalName(), columnInfo.getTabAlias(), false));
            if (!first) {
                colNames = colNames + ",";
                colTypes = colTypes + ",";
            }
            first = false;
            colNames = colNames + newColName;
            colTypes = colTypes + valueCols.get(k).getTypeString();
        }
        // we are putting join keys at last part of the spilled table
        for (int k = 0; k < joinKeys.size(); k++) {
            if (!first) {
                colNames = colNames + ",";
                colTypes = colTypes + ",";
            }
            first = false;
            colNames = colNames + joinKeys.get(k);
            colTypes = colTypes + joinKeyTypes.get(k);
            ColumnInfo columnInfo = new ColumnInfo(joinKeys.get(k), TypeInfoFactory.getPrimitiveTypeInfo(joinKeyTypes.get(k)), alias.toString(), false);
            columnInfos.add(columnInfo);
            newKeyExpr.add(new ExprNodeColumnDesc(columnInfo.getType(), columnInfo.getInternalName(), columnInfo.getTabAlias(), false));
        }
        newJoinValues.put(alias, newValueExpr);
        newJoinKeys.put(alias, newKeyExpr);
        tableDescList.put(alias, Utilities.getTableDesc(colNames, colTypes));
        rowSchemaList.put(alias, new RowSchema(columnInfos));
        // construct value table Desc
        String valueColNames = "";
        String valueColTypes = "";
        first = true;
        for (int k = 0; k < columnSize; k++) {
            // any name, it does not matter.
            String newColName = i + "_VALUE_" + k;
            if (!first) {
                valueColNames = valueColNames + ",";
                valueColTypes = valueColTypes + ",";
            }
            valueColNames = valueColNames + newColName;
            valueColTypes = valueColTypes + valueCols.get(k).getTypeString();
            first = false;
        }
        newJoinValueTblDesc.set((byte) i, Utilities.getTableDesc(valueColNames, valueColTypes));
    }
    joinDescriptor.setSkewKeysValuesTables(tableDescList);
    joinDescriptor.setKeyTableDesc(keyTblDesc);
    // create N-1 map join tasks
    HashMap<Path, Task<? extends Serializable>> bigKeysDirToTaskMap = new HashMap<Path, Task<? extends Serializable>>();
    List<Serializable> listWorks = new ArrayList<Serializable>();
    List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
    for (int i = 0; i < numAliases - 1; i++) {
        Byte src = tags[i];
        HiveConf hiveConf = new HiveConf(parseCtx.getConf(), GenSparkSkewJoinProcessor.class);
        SparkWork sparkWork = new SparkWork(parseCtx.getConf().getVar(HiveConf.ConfVars.HIVEQUERYID));
        Task<? extends Serializable> skewJoinMapJoinTask = TaskFactory.get(sparkWork, hiveConf);
        skewJoinMapJoinTask.setFetchSource(currTask.isFetchSource());
        // create N TableScans
        Operator<? extends OperatorDesc>[] parentOps = new TableScanOperator[tags.length];
        for (int k = 0; k < tags.length; k++) {
            Operator<? extends OperatorDesc> ts = GenMapRedUtils.createTemporaryTableScanOperator(joinOp.getCompilationOpContext(), rowSchemaList.get((byte) k));
            ((TableScanOperator) ts).setTableDesc(tableDescList.get((byte) k));
            parentOps[k] = ts;
        }
        // create the MapJoinOperator
        String dumpFilePrefix = "mapfile" + PlanUtils.getCountForMapJoinDumpFilePrefix();
        MapJoinDesc mapJoinDescriptor = new MapJoinDesc(newJoinKeys, keyTblDesc, newJoinValues, newJoinValueTblDesc, newJoinValueTblDesc, joinDescriptor.getOutputColumnNames(), i, joinDescriptor.getConds(), joinDescriptor.getFilters(), joinDescriptor.getNoOuterJoin(), dumpFilePrefix);
        mapJoinDescriptor.setTagOrder(tags);
        mapJoinDescriptor.setHandleSkewJoin(false);
        mapJoinDescriptor.setNullSafes(joinDescriptor.getNullSafes());
        // temporarily, mark it as child of all the TS
        MapJoinOperator mapJoinOp = (MapJoinOperator) OperatorFactory.getAndMakeChild(joinOp.getCompilationOpContext(), mapJoinDescriptor, null, parentOps);
        // clone the original join operator, and replace it with the MJ
        // this makes sure MJ has the same downstream operator plan as the original join
        List<Operator<?>> reducerList = new ArrayList<Operator<?>>();
        reducerList.add(reduceWork.getReducer());
        Operator<? extends OperatorDesc> reducer = SerializationUtilities.cloneOperatorTree(reducerList).get(0);
        Preconditions.checkArgument(reducer instanceof JoinOperator, "Reducer should be join operator, but actually is " + reducer.getName());
        JoinOperator cloneJoinOp = (JoinOperator) reducer;
        List<Operator<? extends OperatorDesc>> childOps = cloneJoinOp.getChildOperators();
        for (Operator<? extends OperatorDesc> childOp : childOps) {
            childOp.replaceParent(cloneJoinOp, mapJoinOp);
        }
        mapJoinOp.setChildOperators(childOps);
        // set memory usage for the MJ operator
        setMemUsage(mapJoinOp, skewJoinMapJoinTask, parseCtx);
        // create N MapWorks and add them to the SparkWork
        MapWork bigMapWork = null;
        Map<Byte, Path> smallTblDirs = smallKeysDirMap.get(src);
        for (int j = 0; j < tags.length; j++) {
            MapWork mapWork = PlanUtils.getMapRedWork().getMapWork();
            sparkWork.add(mapWork);
            // This code has been only added for testing
            boolean mapperCannotSpanPartns = parseCtx.getConf().getBoolVar(HiveConf.ConfVars.HIVE_MAPPER_CANNOT_SPAN_MULTIPLE_PARTITIONS);
            mapWork.setMapperCannotSpanPartns(mapperCannotSpanPartns);
            Operator<? extends OperatorDesc> tableScan = parentOps[j];
            String alias = tags[j].toString();
            ArrayList<String> aliases = new ArrayList<String>();
            aliases.add(alias);
            Path path;
            if (j == i) {
                path = bigKeysDirMap.get(tags[j]);
                bigKeysDirToTaskMap.put(path, skewJoinMapJoinTask);
                bigMapWork = mapWork;
            } else {
                path = smallTblDirs.get(tags[j]);
            }
            mapWork.addPathToAlias(path, aliases);
            mapWork.getAliasToWork().put(alias, tableScan);
            PartitionDesc partitionDesc = new PartitionDesc(tableDescList.get(tags[j]), null);
            mapWork.addPathToPartitionInfo(path, partitionDesc);
            mapWork.getAliasToPartnInfo().put(alias, partitionDesc);
            mapWork.setName("Map " + GenSparkUtils.getUtils().getNextSeqNumber());
        }
        // connect all small dir map work to the big dir map work
        Preconditions.checkArgument(bigMapWork != null, "Haven't identified big dir MapWork");
        // these 2 flags are intended only for the big-key map work
        bigMapWork.setNumMapTasks(HiveConf.getIntVar(hiveConf, HiveConf.ConfVars.HIVESKEWJOINMAPJOINNUMMAPTASK));
        bigMapWork.setMinSplitSize(HiveConf.getLongVar(hiveConf, HiveConf.ConfVars.HIVESKEWJOINMAPJOINMINSPLIT));
        // use HiveInputFormat so that we can control the number of map tasks
        bigMapWork.setInputformat(HiveInputFormat.class.getName());
        for (BaseWork work : sparkWork.getRoots()) {
            Preconditions.checkArgument(work instanceof MapWork, "All root work should be MapWork, but got " + work.getClass().getSimpleName());
            if (work != bigMapWork) {
                sparkWork.connect(work, bigMapWork, new SparkEdgeProperty(SparkEdgeProperty.SHUFFLE_NONE));
            }
        }
        // insert SparkHashTableSink and Dummy operators
        for (int j = 0; j < tags.length; j++) {
            if (j != i) {
                insertSHTS(tags[j], (TableScanOperator) parentOps[j], bigMapWork);
            }
        }
        listWorks.add(skewJoinMapJoinTask.getWork());
        listTasks.add(skewJoinMapJoinTask);
    }
    if (children != null) {
        for (Task<? extends Serializable> tsk : listTasks) {
            for (Task<? extends Serializable> oldChild : children) {
                tsk.addDependentTask(oldChild);
            }
        }
        currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
        for (Task<? extends Serializable> oldChild : children) {
            oldChild.getParentTasks().remove(currTask);
        }
        listTasks.addAll(children);
        for (Task<? extends Serializable> oldChild : children) {
            listWorks.add(oldChild.getWork());
        }
    }
    ConditionalResolverSkewJoin.ConditionalResolverSkewJoinCtx context = new ConditionalResolverSkewJoin.ConditionalResolverSkewJoinCtx(bigKeysDirToTaskMap, children);
    ConditionalWork cndWork = new ConditionalWork(listWorks);
    ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork, parseCtx.getConf());
    cndTsk.setListTasks(listTasks);
    cndTsk.setResolver(new ConditionalResolverSkewJoin());
    cndTsk.setResolverCtx(context);
    currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
    currTask.addDependentTask(cndTsk);
}
Also used : MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) SparkTask(org.apache.hadoop.hive.ql.exec.spark.SparkTask) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) Task(org.apache.hadoop.hive.ql.exec.Task) Serializable(java.io.Serializable) TableScanOperator(org.apache.hadoop.hive.ql.exec.TableScanOperator) HashMap(java.util.HashMap) ArrayList(java.util.ArrayList) ConditionalWork(org.apache.hadoop.hive.ql.plan.ConditionalWork) ColumnInfo(org.apache.hadoop.hive.ql.exec.ColumnInfo) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) List(java.util.List) ArrayList(java.util.ArrayList) HiveConf(org.apache.hadoop.hive.conf.HiveConf) ExprNodeDesc(org.apache.hadoop.hive.ql.plan.ExprNodeDesc) BaseWork(org.apache.hadoop.hive.ql.plan.BaseWork) ConditionalResolverSkewJoin(org.apache.hadoop.hive.ql.plan.ConditionalResolverSkewJoin) MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) RowSchema(org.apache.hadoop.hive.ql.exec.RowSchema) TypeInfo(org.apache.hadoop.hive.serde2.typeinfo.TypeInfo) TableDesc(org.apache.hadoop.hive.ql.plan.TableDesc) MapJoinDesc(org.apache.hadoop.hive.ql.plan.MapJoinDesc) JoinDesc(org.apache.hadoop.hive.ql.plan.JoinDesc) Map(java.util.Map) HashMap(java.util.HashMap) OperatorDesc(org.apache.hadoop.hive.ql.plan.OperatorDesc) MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) HashTableDummyOperator(org.apache.hadoop.hive.ql.exec.HashTableDummyOperator) SparkHashTableSinkOperator(org.apache.hadoop.hive.ql.exec.SparkHashTableSinkOperator) JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) TableScanOperator(org.apache.hadoop.hive.ql.exec.TableScanOperator) Operator(org.apache.hadoop.hive.ql.exec.Operator) HiveInputFormat(org.apache.hadoop.hive.ql.io.HiveInputFormat) ExprNodeColumnDesc(org.apache.hadoop.hive.ql.plan.ExprNodeColumnDesc) Path(org.apache.hadoop.fs.Path) MapJoinDesc(org.apache.hadoop.hive.ql.plan.MapJoinDesc) SparkTask(org.apache.hadoop.hive.ql.exec.spark.SparkTask) SparkWork(org.apache.hadoop.hive.ql.plan.SparkWork) MapWork(org.apache.hadoop.hive.ql.plan.MapWork) SparkEdgeProperty(org.apache.hadoop.hive.ql.plan.SparkEdgeProperty) PartitionDesc(org.apache.hadoop.hive.ql.plan.PartitionDesc)

Example 5 with ConditionalWork

use of org.apache.hadoop.hive.ql.plan.ConditionalWork in project hive by apache.

the class CommonJoinTaskDispatcher method processCurrentTask.

@Override
public Task<? extends Serializable> processCurrentTask(MapRedTask currTask, ConditionalTask conditionalTask, Context context) throws SemanticException {
    // whether it contains common join op; if contains, return this common join op
    JoinOperator joinOp = getJoinOp(currTask);
    if (joinOp == null || joinOp.getConf().isFixedAsSorted()) {
        return null;
    }
    currTask.setTaskTag(Task.COMMON_JOIN);
    MapWork currWork = currTask.getWork().getMapWork();
    // create conditional work list and task list
    List<Serializable> listWorks = new ArrayList<Serializable>();
    List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
    // create task to aliases mapping and alias to input file mapping for resolver
    // Must be deterministic order map for consistent q-test output across Java versions
    HashMap<Task<? extends Serializable>, Set<String>> taskToAliases = new LinkedHashMap<Task<? extends Serializable>, Set<String>>();
    HashMap<Path, ArrayList<String>> pathToAliases = currWork.getPathToAliases();
    Map<String, Operator<? extends OperatorDesc>> aliasToWork = currWork.getAliasToWork();
    // get parseCtx for this Join Operator
    ParseContext parseCtx = physicalContext.getParseContext();
    // start to generate multiple map join tasks
    JoinDesc joinDesc = joinOp.getConf();
    if (aliasToSize == null) {
        aliasToSize = new HashMap<String, Long>();
    }
    try {
        long aliasTotalKnownInputSize = getTotalKnownInputSize(context, currWork, pathToAliases, aliasToSize);
        Set<Integer> bigTableCandidates = MapJoinProcessor.getBigTableCandidates(joinDesc.getConds());
        // no table could be the big table; there is no need to convert
        if (bigTableCandidates.isEmpty()) {
            return null;
        }
        // if any of bigTableCandidates is from multi-sourced, bigTableCandidates should
        // only contain multi-sourced because multi-sourced cannot be hashed or direct readable
        bigTableCandidates = multiInsertBigTableCheck(joinOp, bigTableCandidates);
        Configuration conf = context.getConf();
        // If sizes of at least n-1 tables in a n-way join is known, and their sum is smaller than
        // the threshold size, convert the join into map-join and don't create a conditional task
        boolean convertJoinMapJoin = HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVECONVERTJOINNOCONDITIONALTASK);
        int bigTablePosition = -1;
        if (convertJoinMapJoin) {
            // This is the threshold that the user has specified to fit in mapjoin
            long mapJoinSize = HiveConf.getLongVar(conf, HiveConf.ConfVars.HIVECONVERTJOINNOCONDITIONALTASKTHRESHOLD);
            Long bigTableSize = null;
            Set<String> aliases = aliasToWork.keySet();
            for (int tablePosition : bigTableCandidates) {
                Operator<?> parent = joinOp.getParentOperators().get(tablePosition);
                Set<String> participants = GenMapRedUtils.findAliases(currWork, parent);
                long sumOfOthers = Utilities.sumOfExcept(aliasToSize, aliases, participants);
                if (sumOfOthers < 0 || sumOfOthers > mapJoinSize) {
                    // some small alias is not known or too big
                    continue;
                }
                if (bigTableSize == null && bigTablePosition >= 0 && tablePosition < bigTablePosition) {
                    // prefer right most alias
                    continue;
                }
                long aliasSize = Utilities.sumOf(aliasToSize, participants);
                if (bigTableSize == null || bigTableSize < 0 || (aliasSize >= 0 && aliasSize >= bigTableSize)) {
                    bigTablePosition = tablePosition;
                    bigTableSize = aliasSize;
                }
            }
        }
        currWork.setLeftInputJoin(joinOp.getConf().isLeftInputJoin());
        currWork.setBaseSrc(joinOp.getConf().getBaseSrc());
        currWork.setMapAliases(joinOp.getConf().getMapAliases());
        if (bigTablePosition >= 0) {
            // create map join task and set big table as bigTablePosition
            MapRedTask newTask = convertTaskToMapJoinTask(currTask.getWork(), bigTablePosition);
            newTask.setTaskTag(Task.MAPJOIN_ONLY_NOBACKUP);
            newTask.setFetchSource(currTask.isFetchSource());
            replaceTask(currTask, newTask);
            // joined with multiple small tables on different keys
            if ((newTask.getChildTasks() != null) && (newTask.getChildTasks().size() == 1)) {
                mergeMapJoinTaskIntoItsChildMapRedTask(newTask, conf);
            }
            return newTask;
        }
        long ThresholdOfSmallTblSizeSum = HiveConf.getLongVar(conf, HiveConf.ConfVars.HIVESMALLTABLESFILESIZE);
        for (int pos = 0; pos < joinOp.getNumParent(); pos++) {
            // this table cannot be big table
            if (!bigTableCandidates.contains(pos)) {
                continue;
            }
            Operator<?> startOp = joinOp.getParentOperators().get(pos);
            Set<String> aliases = GenMapRedUtils.findAliases(currWork, startOp);
            long aliasKnownSize = Utilities.sumOf(aliasToSize, aliases);
            if (cannotConvert(aliasKnownSize, aliasTotalKnownInputSize, ThresholdOfSmallTblSizeSum)) {
                continue;
            }
            MapredWork newWork = SerializationUtilities.clonePlan(currTask.getWork());
            // create map join task and set big table as i
            MapRedTask newTask = convertTaskToMapJoinTask(newWork, pos);
            // add into conditional task
            listWorks.add(newTask.getWork());
            listTasks.add(newTask);
            newTask.setTaskTag(Task.CONVERTED_MAPJOIN);
            newTask.setFetchSource(currTask.isFetchSource());
            // set up backup task
            newTask.setBackupTask(currTask);
            newTask.setBackupChildrenTasks(currTask.getChildTasks());
            // put the mapping task to aliases
            taskToAliases.put(newTask, aliases);
        }
    } catch (Exception e) {
        throw new SemanticException("Generate Map Join Task Error: " + e.getMessage(), e);
    }
    if (listTasks.isEmpty()) {
        return currTask;
    }
    // insert current common join task to conditional task
    listWorks.add(currTask.getWork());
    listTasks.add(currTask);
    // clear JoinTree and OP Parse Context
    currWork.setLeftInputJoin(false);
    currWork.setBaseSrc(null);
    currWork.setMapAliases(null);
    // create conditional task and insert conditional task into task tree
    ConditionalWork cndWork = new ConditionalWork(listWorks);
    ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork, parseCtx.getConf());
    cndTsk.setListTasks(listTasks);
    // set resolver and resolver context
    cndTsk.setResolver(new ConditionalResolverCommonJoin());
    ConditionalResolverCommonJoinCtx resolverCtx = new ConditionalResolverCommonJoinCtx();
    resolverCtx.setPathToAliases(pathToAliases);
    resolverCtx.setAliasToKnownSize(aliasToSize);
    resolverCtx.setTaskToAliases(taskToAliases);
    resolverCtx.setCommonJoinTask(currTask);
    resolverCtx.setLocalTmpDir(context.getLocalScratchDir(false));
    resolverCtx.setHdfsTmpDir(context.getMRScratchDir());
    cndTsk.setResolverCtx(resolverCtx);
    // replace the current task with the new generated conditional task
    replaceTaskWithConditionalTask(currTask, cndTsk);
    return cndTsk;
}
Also used : JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) LateralViewForwardOperator(org.apache.hadoop.hive.ql.exec.LateralViewForwardOperator) FileSinkOperator(org.apache.hadoop.hive.ql.exec.FileSinkOperator) JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) TableScanOperator(org.apache.hadoop.hive.ql.exec.TableScanOperator) Operator(org.apache.hadoop.hive.ql.exec.Operator) Serializable(java.io.Serializable) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) Task(org.apache.hadoop.hive.ql.exec.Task) MapRedTask(org.apache.hadoop.hive.ql.exec.mr.MapRedTask) HashSet(java.util.HashSet) Set(java.util.Set) Configuration(org.apache.hadoop.conf.Configuration) ArrayList(java.util.ArrayList) ConditionalWork(org.apache.hadoop.hive.ql.plan.ConditionalWork) LinkedHashMap(java.util.LinkedHashMap) MapRedTask(org.apache.hadoop.hive.ql.exec.mr.MapRedTask) ConditionalResolverCommonJoinCtx(org.apache.hadoop.hive.ql.plan.ConditionalResolverCommonJoin.ConditionalResolverCommonJoinCtx) MapredWork(org.apache.hadoop.hive.ql.plan.MapredWork) ConditionalTask(org.apache.hadoop.hive.ql.exec.ConditionalTask) ConditionalResolverCommonJoin(org.apache.hadoop.hive.ql.plan.ConditionalResolverCommonJoin) SemanticException(org.apache.hadoop.hive.ql.parse.SemanticException) Path(org.apache.hadoop.fs.Path) SemanticException(org.apache.hadoop.hive.ql.parse.SemanticException) UnsupportedEncodingException(java.io.UnsupportedEncodingException) MapWork(org.apache.hadoop.hive.ql.plan.MapWork) ParseContext(org.apache.hadoop.hive.ql.parse.ParseContext) OperatorDesc(org.apache.hadoop.hive.ql.plan.OperatorDesc) JoinDesc(org.apache.hadoop.hive.ql.plan.JoinDesc)

Aggregations

Serializable (java.io.Serializable)5 ArrayList (java.util.ArrayList)5 ConditionalTask (org.apache.hadoop.hive.ql.exec.ConditionalTask)5 Task (org.apache.hadoop.hive.ql.exec.Task)5 ConditionalWork (org.apache.hadoop.hive.ql.plan.ConditionalWork)5 Path (org.apache.hadoop.fs.Path)4 MapWork (org.apache.hadoop.hive.ql.plan.MapWork)4 HashMap (java.util.HashMap)3 LinkedHashMap (java.util.LinkedHashMap)3 JoinOperator (org.apache.hadoop.hive.ql.exec.JoinOperator)3 Operator (org.apache.hadoop.hive.ql.exec.Operator)3 TableScanOperator (org.apache.hadoop.hive.ql.exec.TableScanOperator)3 MapRedTask (org.apache.hadoop.hive.ql.exec.mr.MapRedTask)3 JoinDesc (org.apache.hadoop.hive.ql.plan.JoinDesc)3 OperatorDesc (org.apache.hadoop.hive.ql.plan.OperatorDesc)3 UnsupportedEncodingException (java.io.UnsupportedEncodingException)2 List (java.util.List)2 Map (java.util.Map)2 Set (java.util.Set)2 Configuration (org.apache.hadoop.conf.Configuration)2