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Example 21 with PartitionDesc

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

the class CombineHiveInputFormat method getCombineSplits.

/**
   * Create Hive splits based on CombineFileSplit.
   */
private InputSplit[] getCombineSplits(JobConf job, int numSplits, Map<Path, PartitionDesc> pathToPartitionInfo) throws IOException {
    init(job);
    Map<Path, ArrayList<String>> pathToAliases = mrwork.getPathToAliases();
    Map<String, Operator<? extends OperatorDesc>> aliasToWork = mrwork.getAliasToWork();
    CombineFileInputFormatShim combine = ShimLoader.getHadoopShims().getCombineFileInputFormat();
    InputSplit[] splits = null;
    if (combine == null) {
        splits = super.getSplits(job, numSplits);
        return splits;
    }
    if (combine.getInputPathsShim(job).length == 0) {
        throw new IOException("No input paths specified in job");
    }
    ArrayList<InputSplit> result = new ArrayList<InputSplit>();
    // combine splits only from same tables and same partitions. Do not combine splits from multiple
    // tables or multiple partitions.
    Path[] paths = StringInternUtils.internUriStringsInPathArray(combine.getInputPathsShim(job));
    List<Path> inpDirs = new ArrayList<Path>();
    List<Path> inpFiles = new ArrayList<Path>();
    Map<CombinePathInputFormat, CombineFilter> poolMap = new HashMap<CombinePathInputFormat, CombineFilter>();
    Set<Path> poolSet = new HashSet<Path>();
    for (Path path : paths) {
        PartitionDesc part = HiveFileFormatUtils.getPartitionDescFromPathRecursively(pathToPartitionInfo, path, IOPrepareCache.get().allocatePartitionDescMap());
        TableDesc tableDesc = part.getTableDesc();
        if ((tableDesc != null) && tableDesc.isNonNative()) {
            return super.getSplits(job, numSplits);
        }
        // Use HiveInputFormat if any of the paths is not splittable
        Class inputFormatClass = part.getInputFileFormatClass();
        String inputFormatClassName = inputFormatClass.getName();
        InputFormat inputFormat = getInputFormatFromCache(inputFormatClass, job);
        String deserializerClassName = null;
        try {
            deserializerClassName = part.getDeserializer(job).getClass().getName();
        } catch (Exception e) {
        // ignore
        }
        FileSystem inpFs = path.getFileSystem(job);
        //don't combine if inputformat is a SymlinkTextInputFormat
        if (inputFormat instanceof SymlinkTextInputFormat) {
            splits = super.getSplits(job, numSplits);
            return splits;
        }
        Path filterPath = path;
        // Does a pool exist for this path already
        CombineFilter f = null;
        List<Operator<? extends OperatorDesc>> opList = null;
        if (!mrwork.isMapperCannotSpanPartns()) {
            //if mapper can span partitions, make sure a splits does not contain multiple
            // opList + inputFormatClassName + deserializerClassName combination
            // This is done using the Map of CombinePathInputFormat to PathFilter
            opList = HiveFileFormatUtils.doGetWorksFromPath(pathToAliases, aliasToWork, filterPath);
            CombinePathInputFormat combinePathInputFormat = new CombinePathInputFormat(opList, inputFormatClassName, deserializerClassName);
            f = poolMap.get(combinePathInputFormat);
            if (f == null) {
                f = new CombineFilter(filterPath);
                LOG.info("CombineHiveInputSplit creating pool for " + path + "; using filter path " + filterPath);
                combine.createPool(job, f);
                poolMap.put(combinePathInputFormat, f);
            } else {
                LOG.info("CombineHiveInputSplit: pool is already created for " + path + "; using filter path " + filterPath);
                f.addPath(filterPath);
            }
        } else {
            // but won't cross multiple partitions if the user has asked so.
            if (!path.getFileSystem(job).getFileStatus(path).isDir()) {
                // path is not directory
                filterPath = path.getParent();
                inpFiles.add(path);
                poolSet.add(filterPath);
            } else {
                inpDirs.add(path);
            }
        }
    }
    // Processing directories
    List<CombineFileSplit> iss = new ArrayList<CombineFileSplit>();
    if (!mrwork.isMapperCannotSpanPartns()) {
        //mapper can span partitions
        //combine into as few as one split, subject to the PathFilters set
        // using combine.createPool.
        iss = Arrays.asList(combine.getSplits(job, 1));
    } else {
        for (Path path : inpDirs) {
            processPaths(job, combine, iss, path);
        }
        if (inpFiles.size() > 0) {
            // Processing files
            for (Path filterPath : poolSet) {
                combine.createPool(job, new CombineFilter(filterPath));
            }
            processPaths(job, combine, iss, inpFiles.toArray(new Path[0]));
        }
    }
    if (mrwork.getNameToSplitSample() != null && !mrwork.getNameToSplitSample().isEmpty()) {
        iss = sampleSplits(iss);
    }
    for (CombineFileSplit is : iss) {
        CombineHiveInputSplit csplit = new CombineHiveInputSplit(job, is, pathToPartitionInfo);
        result.add(csplit);
    }
    LOG.info("number of splits " + result.size());
    return result.toArray(new CombineHiveInputSplit[result.size()]);
}
Also used : Operator(org.apache.hadoop.hive.ql.exec.Operator) HashMap(java.util.HashMap) ArrayList(java.util.ArrayList) CombineFileSplit(org.apache.hadoop.mapred.lib.CombineFileSplit) CombineFileInputFormatShim(org.apache.hadoop.hive.shims.HadoopShims.CombineFileInputFormatShim) FileSystem(org.apache.hadoop.fs.FileSystem) InputSplit(org.apache.hadoop.mapred.InputSplit) HashSet(java.util.HashSet) Path(org.apache.hadoop.fs.Path) IOException(java.io.IOException) IOException(java.io.IOException) ExecutionException(java.util.concurrent.ExecutionException) InputFormat(org.apache.hadoop.mapred.InputFormat) FileInputFormat(org.apache.hadoop.mapred.FileInputFormat) PartitionDesc(org.apache.hadoop.hive.ql.plan.PartitionDesc) TableDesc(org.apache.hadoop.hive.ql.plan.TableDesc) OperatorDesc(org.apache.hadoop.hive.ql.plan.OperatorDesc)

Example 22 with PartitionDesc

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

the class GenMapRedUtils method getMapRedWorkFromConf.

/**
   * create a new plan and return. The pan won't contain the name to split
   * sample information in parse context.
   *
   * @return the new plan
   */
public static MapredWork getMapRedWorkFromConf(HiveConf conf) {
    MapredWork mrWork = new MapredWork();
    MapWork work = mrWork.getMapWork();
    boolean mapperCannotSpanPartns = conf.getBoolVar(HiveConf.ConfVars.HIVE_MAPPER_CANNOT_SPAN_MULTIPLE_PARTITIONS);
    work.setMapperCannotSpanPartns(mapperCannotSpanPartns);
    work.setPathToAliases(new LinkedHashMap<Path, ArrayList<String>>());
    work.setPathToPartitionInfo(new LinkedHashMap<Path, PartitionDesc>());
    work.setAliasToWork(new LinkedHashMap<String, Operator<? extends OperatorDesc>>());
    return mrWork;
}
Also used : Path(org.apache.hadoop.fs.Path) ReduceSinkOperator(org.apache.hadoop.hive.ql.exec.ReduceSinkOperator) DemuxOperator(org.apache.hadoop.hive.ql.exec.DemuxOperator) JoinOperator(org.apache.hadoop.hive.ql.exec.JoinOperator) TableScanOperator(org.apache.hadoop.hive.ql.exec.TableScanOperator) Operator(org.apache.hadoop.hive.ql.exec.Operator) MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) UnionOperator(org.apache.hadoop.hive.ql.exec.UnionOperator) FileSinkOperator(org.apache.hadoop.hive.ql.exec.FileSinkOperator) SMBMapJoinOperator(org.apache.hadoop.hive.ql.exec.SMBMapJoinOperator) MapredWork(org.apache.hadoop.hive.ql.plan.MapredWork) MapWork(org.apache.hadoop.hive.ql.plan.MapWork) ArrayList(java.util.ArrayList) PartitionDesc(org.apache.hadoop.hive.ql.plan.PartitionDesc) OperatorDesc(org.apache.hadoop.hive.ql.plan.OperatorDesc)

Example 23 with PartitionDesc

use of org.apache.hadoop.hive.ql.plan.PartitionDesc 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 24 with PartitionDesc

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

the class SortMergeJoinTaskDispatcher method genSMBJoinWork.

// Convert the work in the SMB plan to a regular join
// Note that the operator tree is not fixed, only the path/alias mappings in the
// plan are fixed. The operator tree will still contain the SMBJoinOperator
private void genSMBJoinWork(MapWork currWork, SMBMapJoinOperator smbJoinOp) {
    // Remove the paths which are not part of aliasToPartitionInfo
    Map<String, PartitionDesc> aliasToPartitionInfo = currWork.getAliasToPartnInfo();
    List<Path> removePaths = new ArrayList<>();
    for (Map.Entry<Path, ArrayList<String>> entry : currWork.getPathToAliases().entrySet()) {
        boolean keepPath = false;
        for (String alias : entry.getValue()) {
            if (aliasToPartitionInfo.containsKey(alias)) {
                keepPath = true;
                break;
            }
        }
        // Remove if the path is not present
        if (!keepPath) {
            removePaths.add(entry.getKey());
        }
    }
    List<String> removeAliases = new ArrayList<String>();
    for (Path removePath : removePaths) {
        removeAliases.addAll(currWork.getPathToAliases().get(removePath));
        currWork.removePathToAlias(removePath);
        currWork.removePathToPartitionInfo(removePath);
    }
    for (String alias : removeAliases) {
        currWork.getAliasToPartnInfo().remove(alias);
        currWork.getAliasToWork().remove(alias);
    }
    // Get the MapredLocalWork
    MapredLocalWork localWork = smbJoinOp.getConf().getLocalWork();
    for (Map.Entry<String, Operator<? extends OperatorDesc>> entry : localWork.getAliasToWork().entrySet()) {
        String alias = entry.getKey();
        Operator<? extends OperatorDesc> op = entry.getValue();
        FetchWork fetchWork = localWork.getAliasToFetchWork().get(alias);
        // Add the entry in mapredwork
        currWork.getAliasToWork().put(alias, op);
        PartitionDesc partitionInfo = currWork.getAliasToPartnInfo().get(alias);
        if (fetchWork.getTblDir() != null) {
            currWork.mergeAliasedInput(alias, fetchWork.getTblDir(), partitionInfo);
        } else {
            for (Path pathDir : fetchWork.getPartDir()) {
                currWork.mergeAliasedInput(alias, pathDir, partitionInfo);
            }
        }
    }
    // Remove the dummy store operator from the tree
    for (Operator<? extends OperatorDesc> parentOp : smbJoinOp.getParentOperators()) {
        if (parentOp instanceof DummyStoreOperator) {
            Operator<? extends OperatorDesc> grandParentOp = parentOp.getParentOperators().get(0);
            smbJoinOp.replaceParent(parentOp, grandParentOp);
            grandParentOp.setChildOperators(parentOp.getChildOperators());
            parentOp.setParentOperators(null);
            parentOp.setParentOperators(null);
        }
    }
}
Also used : Path(org.apache.hadoop.fs.Path) ReduceSinkOperator(org.apache.hadoop.hive.ql.exec.ReduceSinkOperator) MapJoinOperator(org.apache.hadoop.hive.ql.exec.MapJoinOperator) FileSinkOperator(org.apache.hadoop.hive.ql.exec.FileSinkOperator) SMBMapJoinOperator(org.apache.hadoop.hive.ql.exec.SMBMapJoinOperator) Operator(org.apache.hadoop.hive.ql.exec.Operator) DummyStoreOperator(org.apache.hadoop.hive.ql.exec.DummyStoreOperator) DummyStoreOperator(org.apache.hadoop.hive.ql.exec.DummyStoreOperator) ArrayList(java.util.ArrayList) MapredLocalWork(org.apache.hadoop.hive.ql.plan.MapredLocalWork) FetchWork(org.apache.hadoop.hive.ql.plan.FetchWork) PartitionDesc(org.apache.hadoop.hive.ql.plan.PartitionDesc) HashMap(java.util.HashMap) LinkedHashMap(java.util.LinkedHashMap) Map(java.util.Map) OperatorDesc(org.apache.hadoop.hive.ql.plan.OperatorDesc)

Example 25 with PartitionDesc

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

the class VectorDeserializeOrcWriter method create.

// TODO: if more writers are added, separate out an EncodingWriterFactory
public static EncodingWriter create(InputFormat<?, ?> sourceIf, Deserializer serDe, Map<Path, PartitionDesc> parts, Configuration daemonConf, Configuration jobConf, Path splitPath, StructObjectInspector sourceOi, List<Integer> sourceIncludes, boolean[] cacheIncludes, int allocSize) throws IOException {
    // Vector SerDe can be disabled both on client and server side.
    if (!HiveConf.getBoolVar(daemonConf, ConfVars.LLAP_IO_ENCODE_VECTOR_SERDE_ENABLED) || !HiveConf.getBoolVar(jobConf, ConfVars.LLAP_IO_ENCODE_VECTOR_SERDE_ENABLED) || !(sourceIf instanceof TextInputFormat) || !(serDe instanceof LazySimpleSerDe)) {
        return new DeserializerOrcWriter(serDe, sourceOi, allocSize);
    }
    Path path = splitPath.getFileSystem(daemonConf).makeQualified(splitPath);
    PartitionDesc partDesc = HiveFileFormatUtils.getPartitionDescFromPathRecursively(parts, path, null);
    if (partDesc == null) {
        LlapIoImpl.LOG.info("Not using VertorDeserializeOrcWriter: no partition desc for " + path);
        return new DeserializerOrcWriter(serDe, sourceOi, allocSize);
    }
    Properties tblProps = partDesc.getTableDesc().getProperties();
    if ("true".equalsIgnoreCase(tblProps.getProperty(serdeConstants.SERIALIZATION_LAST_COLUMN_TAKES_REST))) {
        LlapIoImpl.LOG.info("Not using VertorDeserializeOrcWriter due to " + serdeConstants.SERIALIZATION_LAST_COLUMN_TAKES_REST);
        return new DeserializerOrcWriter(serDe, sourceOi, allocSize);
    }
    for (StructField sf : sourceOi.getAllStructFieldRefs()) {
        Category c = sf.getFieldObjectInspector().getCategory();
        if (c != Category.PRIMITIVE) {
            LlapIoImpl.LOG.info("Not using VertorDeserializeOrcWriter: " + c + " is not supported");
            return new DeserializerOrcWriter(serDe, sourceOi, allocSize);
        }
    }
    LlapIoImpl.LOG.info("Creating VertorDeserializeOrcWriter for " + path);
    return new VectorDeserializeOrcWriter(daemonConf, tblProps, sourceOi, sourceIncludes, cacheIncludes, allocSize);
}
Also used : DeserializerOrcWriter(org.apache.hadoop.hive.llap.io.encoded.SerDeEncodedDataReader.DeserializerOrcWriter) Path(org.apache.hadoop.fs.Path) StructField(org.apache.hadoop.hive.serde2.objectinspector.StructField) Category(org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector.Category) TextInputFormat(org.apache.hadoop.mapred.TextInputFormat) LazySimpleSerDe(org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe) PartitionDesc(org.apache.hadoop.hive.ql.plan.PartitionDesc) Properties(java.util.Properties)

Aggregations

PartitionDesc (org.apache.hadoop.hive.ql.plan.PartitionDesc)58 Path (org.apache.hadoop.fs.Path)47 ArrayList (java.util.ArrayList)31 TableDesc (org.apache.hadoop.hive.ql.plan.TableDesc)27 LinkedHashMap (java.util.LinkedHashMap)19 HashMap (java.util.HashMap)14 Map (java.util.Map)13 OperatorDesc (org.apache.hadoop.hive.ql.plan.OperatorDesc)13 JobConf (org.apache.hadoop.mapred.JobConf)13 IOException (java.io.IOException)11 Properties (java.util.Properties)10 Operator (org.apache.hadoop.hive.ql.exec.Operator)10 TableScanOperator (org.apache.hadoop.hive.ql.exec.TableScanOperator)10 MapWork (org.apache.hadoop.hive.ql.plan.MapWork)10 MapredWork (org.apache.hadoop.hive.ql.plan.MapredWork)10 HiveException (org.apache.hadoop.hive.ql.metadata.HiveException)8 Configuration (org.apache.hadoop.conf.Configuration)7 FileSystem (org.apache.hadoop.fs.FileSystem)7 MapJoinOperator (org.apache.hadoop.hive.ql.exec.MapJoinOperator)7 SemanticException (org.apache.hadoop.hive.ql.parse.SemanticException)7