use of org.apache.hadoop.hive.ql.metadata.Partition in project hive by apache.
the class BitmapIndexHandler method getIndexPredicateAnalyzer.
/**
* Instantiate a new predicate analyzer suitable for determining
* whether we can use an index, based on rules for indexes in
* WHERE clauses that we support
*
* @return preconfigured predicate analyzer for WHERE queries
*/
private IndexPredicateAnalyzer getIndexPredicateAnalyzer(List<Index> indexes, Set<Partition> queryPartitions) {
IndexPredicateAnalyzer analyzer = new IndexPredicateAnalyzer();
analyzer.addComparisonOp(GenericUDFOPEqual.class.getName());
analyzer.addComparisonOp(GenericUDFOPLessThan.class.getName());
analyzer.addComparisonOp(GenericUDFOPEqualOrLessThan.class.getName());
analyzer.addComparisonOp(GenericUDFOPGreaterThan.class.getName());
analyzer.addComparisonOp(GenericUDFOPEqualOrGreaterThan.class.getName());
// only return results for columns in the list of indexes
for (Index index : indexes) {
List<FieldSchema> columnSchemas = index.getSd().getCols();
for (FieldSchema column : columnSchemas) {
analyzer.allowColumnName(column.getName());
}
}
// are used during the index query generation
for (Partition part : queryPartitions) {
if (part.getSpec().isEmpty()) {
// empty partitions are from whole tables, so we don't want to add them in
continue;
}
for (String column : part.getSpec().keySet()) {
analyzer.allowColumnName(column);
}
}
return analyzer;
}
use of org.apache.hadoop.hive.ql.metadata.Partition in project hive by apache.
the class HiveLockObject method createFrom.
/**
* Creates a locking object for a table (when partition spec is not provided)
* or a table partition
* @param hiveDB an object to communicate with the metastore
* @param tableName the table to create the locking object on
* @param partSpec the spec of a partition to create the locking object on
* @return the locking object
* @throws HiveException
*/
public static HiveLockObject createFrom(Hive hiveDB, String tableName, Map<String, String> partSpec) throws HiveException {
Table tbl = hiveDB.getTable(tableName);
if (tbl == null) {
throw new HiveException("Table " + tableName + " does not exist ");
}
HiveLockObject obj = null;
if (partSpec == null) {
obj = new HiveLockObject(tbl, null);
} else {
Partition par = hiveDB.getPartition(tbl, partSpec, false);
if (par == null) {
throw new HiveException("Partition " + partSpec + " for table " + tableName + " does not exist");
}
obj = new HiveLockObject(par, null);
}
return obj;
}
use of org.apache.hadoop.hive.ql.metadata.Partition in project hive by apache.
the class HiveTxnManagerImpl method lockTable.
@Override
public int lockTable(Hive db, LockTableDesc lockTbl) throws HiveException {
HiveLockManager lockMgr = getAndCheckLockManager();
HiveLockMode mode = HiveLockMode.valueOf(lockTbl.getMode());
String tabName = lockTbl.getTableName();
Table tbl = db.getTable(tabName);
if (tbl == null) {
throw new HiveException("Table " + tabName + " does not exist ");
}
Map<String, String> partSpec = lockTbl.getPartSpec();
HiveLockObjectData lockData = new HiveLockObjectData(lockTbl.getQueryId(), String.valueOf(System.currentTimeMillis()), "EXPLICIT", lockTbl.getQueryStr());
if (partSpec == null) {
HiveLock lck = lockMgr.lock(new HiveLockObject(tbl, lockData), mode, true);
if (lck == null) {
return 1;
}
return 0;
}
Partition par = db.getPartition(tbl, partSpec, false);
if (par == null) {
throw new HiveException("Partition " + partSpec + " for table " + tabName + " does not exist");
}
HiveLock lck = lockMgr.lock(new HiveLockObject(par, lockData), mode, true);
if (lck == null) {
return 1;
}
return 0;
}
use of org.apache.hadoop.hive.ql.metadata.Partition in project hive by apache.
the class GenMapRedUtils method setMapWork.
/**
* initialize MapWork
*
* @param alias_id
* current alias
* @param topOp
* the top operator of the stack
* @param plan
* map work to initialize
* @param local
* whether you need to add to map-reduce or local work
* @param pList
* pruned partition list. If it is null it will be computed on-the-fly.
* @param inputs
* read entities for the map work
* @param conf
* current instance of hive conf
*/
public static void setMapWork(MapWork plan, ParseContext parseCtx, Set<ReadEntity> inputs, PrunedPartitionList partsList, TableScanOperator tsOp, String alias_id, HiveConf conf, boolean local) throws SemanticException {
ArrayList<Path> partDir = new ArrayList<Path>();
ArrayList<PartitionDesc> partDesc = new ArrayList<PartitionDesc>();
boolean isAcidTable = false;
Path tblDir = null;
plan.setNameToSplitSample(parseCtx.getNameToSplitSample());
if (partsList == null) {
try {
partsList = PartitionPruner.prune(tsOp, parseCtx, alias_id);
isAcidTable = tsOp.getConf().isAcidTable();
} catch (SemanticException e) {
throw e;
}
}
// Generate the map work for this alias_id
// pass both confirmed and unknown partitions through the map-reduce
// framework
Set<Partition> parts = partsList.getPartitions();
PartitionDesc aliasPartnDesc = null;
try {
if (!parts.isEmpty()) {
aliasPartnDesc = Utilities.getPartitionDesc(parts.iterator().next());
}
} catch (HiveException e) {
LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
throw new SemanticException(e.getMessage(), e);
}
// The table does not have any partitions
if (aliasPartnDesc == null) {
aliasPartnDesc = new PartitionDesc(Utilities.getTableDesc(tsOp.getConf().getTableMetadata()), null);
}
Map<String, String> props = tsOp.getConf().getOpProps();
if (props != null) {
Properties target = aliasPartnDesc.getProperties();
target.putAll(props);
}
plan.getAliasToPartnInfo().put(alias_id, aliasPartnDesc);
long sizeNeeded = Integer.MAX_VALUE;
int fileLimit = -1;
if (parseCtx.getGlobalLimitCtx().isEnable()) {
if (isAcidTable) {
LOG.info("Skip Global Limit optimization for ACID table");
parseCtx.getGlobalLimitCtx().disableOpt();
} else {
long sizePerRow = HiveConf.getLongVar(parseCtx.getConf(), HiveConf.ConfVars.HIVELIMITMAXROWSIZE);
sizeNeeded = (parseCtx.getGlobalLimitCtx().getGlobalOffset() + parseCtx.getGlobalLimitCtx().getGlobalLimit()) * sizePerRow;
// for the optimization that reduce number of input file, we limit number
// of files allowed. If more than specific number of files have to be
// selected, we skip this optimization. Since having too many files as
// inputs can cause unpredictable latency. It's not necessarily to be
// cheaper.
fileLimit = HiveConf.getIntVar(parseCtx.getConf(), HiveConf.ConfVars.HIVELIMITOPTLIMITFILE);
if (sizePerRow <= 0 || fileLimit <= 0) {
LOG.info("Skip optimization to reduce input size of 'limit'");
parseCtx.getGlobalLimitCtx().disableOpt();
} else if (parts.isEmpty()) {
LOG.info("Empty input: skip limit optimization");
} else {
LOG.info("Try to reduce input size for 'limit' " + "sizeNeeded: " + sizeNeeded + " file limit : " + fileLimit);
}
}
}
boolean isFirstPart = true;
boolean emptyInput = true;
boolean singlePartition = (parts.size() == 1);
// Track the dependencies for the view. Consider a query like: select * from V;
// where V is a view of the form: select * from T
// The dependencies should include V at depth 0, and T at depth 1 (inferred).
Map<String, ReadEntity> viewToInput = parseCtx.getViewAliasToInput();
ReadEntity parentViewInfo = PlanUtils.getParentViewInfo(alias_id, viewToInput);
// The table should also be considered a part of inputs, even if the table is a
// partitioned table and whether any partition is selected or not
//This read entity is a direct read entity and not an indirect read (that is when
// this is being read because it is a dependency of a view).
boolean isDirectRead = (parentViewInfo == null);
TableDesc tblDesc = null;
boolean initTableDesc = false;
PlanUtils.addPartitionInputs(parts, inputs, parentViewInfo, isDirectRead);
for (Partition part : parts) {
// Later the properties have to come from the partition as opposed
// to from the table in order to support versioning.
Path[] paths = null;
SampleDesc sampleDescr = parseCtx.getOpToSamplePruner().get(tsOp);
// Lookup list bucketing pruner
Map<String, ExprNodeDesc> partToPruner = parseCtx.getOpToPartToSkewedPruner().get(tsOp);
ExprNodeDesc listBucketingPruner = (partToPruner != null) ? partToPruner.get(part.getName()) : null;
if (sampleDescr != null) {
assert (listBucketingPruner == null) : "Sampling and list bucketing can't coexit.";
paths = SamplePruner.prune(part, sampleDescr);
parseCtx.getGlobalLimitCtx().disableOpt();
} else if (listBucketingPruner != null) {
assert (sampleDescr == null) : "Sampling and list bucketing can't coexist.";
/* Use list bucketing prunner's path. */
paths = ListBucketingPruner.prune(parseCtx, part, listBucketingPruner);
} else {
// contain enough size, we change to normal mode.
if (parseCtx.getGlobalLimitCtx().isEnable()) {
if (isFirstPart) {
long sizeLeft = sizeNeeded;
ArrayList<Path> retPathList = new ArrayList<Path>();
SamplePruner.LimitPruneRetStatus status = SamplePruner.limitPrune(part, sizeLeft, fileLimit, retPathList);
if (status.equals(SamplePruner.LimitPruneRetStatus.NoFile)) {
continue;
} else if (status.equals(SamplePruner.LimitPruneRetStatus.NotQualify)) {
LOG.info("Use full input -- first " + fileLimit + " files are more than " + sizeNeeded + " bytes");
parseCtx.getGlobalLimitCtx().disableOpt();
} else {
emptyInput = false;
paths = new Path[retPathList.size()];
int index = 0;
for (Path path : retPathList) {
paths[index++] = path;
}
if (status.equals(SamplePruner.LimitPruneRetStatus.NeedAllFiles) && singlePartition) {
// if all files are needed to meet the size limit, we disable
// optimization. It usually happens for empty table/partition or
// table/partition with only one file. By disabling this
// optimization, we can avoid retrying the query if there is
// not sufficient rows.
parseCtx.getGlobalLimitCtx().disableOpt();
}
}
isFirstPart = false;
} else {
paths = new Path[0];
}
}
if (!parseCtx.getGlobalLimitCtx().isEnable()) {
paths = part.getPath();
}
}
// is it a partitioned table ?
if (!part.getTable().isPartitioned()) {
assert (tblDir == null);
tblDir = paths[0];
if (!initTableDesc) {
tblDesc = Utilities.getTableDesc(part.getTable());
initTableDesc = true;
}
} else if (tblDesc == null) {
if (!initTableDesc) {
tblDesc = Utilities.getTableDesc(part.getTable());
initTableDesc = true;
}
}
if (props != null) {
Properties target = tblDesc.getProperties();
target.putAll(props);
}
for (Path p : paths) {
if (p == null) {
continue;
}
String path = p.toString();
if (LOG.isDebugEnabled()) {
LOG.debug("Adding " + path + " of table" + alias_id);
}
partDir.add(p);
try {
if (part.getTable().isPartitioned()) {
partDesc.add(Utilities.getPartitionDesc(part));
} else {
partDesc.add(Utilities.getPartitionDescFromTableDesc(tblDesc, part, false));
}
} catch (HiveException e) {
LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
throw new SemanticException(e.getMessage(), e);
}
}
}
if (emptyInput) {
parseCtx.getGlobalLimitCtx().disableOpt();
}
Utilities.addSchemaEvolutionToTableScanOperator(partsList.getSourceTable(), tsOp);
Iterator<Path> iterPath = partDir.iterator();
Iterator<PartitionDesc> iterPartnDesc = partDesc.iterator();
if (!local) {
while (iterPath.hasNext()) {
assert iterPartnDesc.hasNext();
Path path = iterPath.next();
PartitionDesc prtDesc = iterPartnDesc.next();
// Add the path to alias mapping
plan.addPathToAlias(path, alias_id);
plan.addPathToPartitionInfo(path, prtDesc);
if (LOG.isDebugEnabled()) {
LOG.debug("Information added for path " + path);
}
}
assert plan.getAliasToWork().get(alias_id) == null;
plan.getAliasToWork().put(alias_id, tsOp);
} else {
// populate local work if needed
MapredLocalWork localPlan = plan.getMapRedLocalWork();
if (localPlan == null) {
localPlan = new MapredLocalWork(new LinkedHashMap<String, Operator<? extends OperatorDesc>>(), new LinkedHashMap<String, FetchWork>());
}
assert localPlan.getAliasToWork().get(alias_id) == null;
assert localPlan.getAliasToFetchWork().get(alias_id) == null;
localPlan.getAliasToWork().put(alias_id, tsOp);
if (tblDir == null) {
tblDesc = Utilities.getTableDesc(partsList.getSourceTable());
localPlan.getAliasToFetchWork().put(alias_id, new FetchWork(partDir, partDesc, tblDesc));
} else {
localPlan.getAliasToFetchWork().put(alias_id, new FetchWork(tblDir, tblDesc));
}
plan.setMapRedLocalWork(localPlan);
}
}
use of org.apache.hadoop.hive.ql.metadata.Partition in project hive by apache.
the class GenMapRedUtils method getInputPathsForPartialScan.
public static List<Path> getInputPathsForPartialScan(TableScanOperator tableScanOp, Appendable aggregationKey) throws SemanticException {
List<Path> inputPaths = new ArrayList<Path>();
switch(tableScanOp.getConf().getTableMetadata().getTableSpec().specType) {
case TABLE_ONLY:
inputPaths.add(tableScanOp.getConf().getTableMetadata().getTableSpec().tableHandle.getPath());
break;
case STATIC_PARTITION:
Partition part = tableScanOp.getConf().getTableMetadata().getTableSpec().partHandle;
try {
aggregationKey.append(Warehouse.makePartPath(part.getSpec()));
} catch (MetaException e) {
throw new SemanticException(ErrorMsg.ANALYZE_TABLE_PARTIALSCAN_AGGKEY.getMsg(part.getDataLocation().toString() + e.getMessage()));
} catch (IOException e) {
throw new RuntimeException(e);
}
inputPaths.add(part.getDataLocation());
break;
default:
assert false;
}
return inputPaths;
}
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