org.apache.hadoop.hive.ql.optimizer.GlobalLimitOptimizer Maven / Gradle / Ivy
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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.hadoop.hive.ql.optimizer;
import java.util.Map;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.ql.Context;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.TableScanOperator;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.metadata.Table;
import org.apache.hadoop.hive.ql.optimizer.ppr.PartitionPruner;
import org.apache.hadoop.hive.ql.parse.GlobalLimitCtx;
import org.apache.hadoop.hive.ql.parse.ParseContext;
import org.apache.hadoop.hive.ql.parse.PrunedPartitionList;
import org.apache.hadoop.hive.ql.parse.QB;
import org.apache.hadoop.hive.ql.parse.QBParseInfo;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.parse.SplitSample;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
/**
* This optimizer is used to reduce the input size for the query for queries which are
* specifying a limit.
*
* For eg. for a query of type:
*
* select expr from T where limit 100;
*
* Most probably, the whole table T need not be scanned.
* Chances are that even if we scan the first file of T, we would get the 100 rows
* needed by this query.
* This optimizer step populates the GlobalLimitCtx which is used later on to prune the inputs.
*/
public class GlobalLimitOptimizer implements Transform {
private final Log LOG = LogFactory.getLog(GlobalLimitOptimizer.class.getName());
public ParseContext transform(ParseContext pctx) throws SemanticException {
Context ctx = pctx.getContext();
Map> topOps = pctx.getTopOps();
GlobalLimitCtx globalLimitCtx = pctx.getGlobalLimitCtx();
Map opToPartPruner = pctx.getOpToPartPruner();
Map nameToSplitSample = pctx.getNameToSplitSample();
Map topToTable = pctx.getTopToTable();
QB qb = pctx.getQB();
HiveConf conf = pctx.getConf();
QBParseInfo qbParseInfo = qb.getParseInfo();
// determine the query qualifies reduce input size for LIMIT
// The query only qualifies when there are only one top operator
// and there is no transformer or UDTF and no block sampling
// is used.
if (ctx.getTryCount() == 0 && topOps.size() == 1
&& !globalLimitCtx.ifHasTransformOrUDTF() &&
nameToSplitSample.isEmpty()) {
// Here we recursively check:
// 1. whether there are exact one LIMIT in the query
// 2. whether there is no aggregation, group-by, distinct, sort by,
// distributed by, or table sampling in any of the sub-query.
// The query only qualifies if both conditions are satisfied.
//
// Example qualified queries:
// CREATE TABLE ... AS SELECT col1, col2 FROM tbl LIMIT ..
// INSERT OVERWRITE TABLE ... SELECT col1, hash(col2), split(col1)
// FROM ... LIMIT...
// SELECT * FROM (SELECT col1 as col2 (SELECT * FROM ...) t1 LIMIT ...) t2);
//
Integer tempGlobalLimit = checkQbpForGlobalLimit(qb);
// query qualify for the optimization
if (tempGlobalLimit != null && tempGlobalLimit != 0) {
TableScanOperator ts = (TableScanOperator) topOps.values().toArray()[0];
Table tab = topToTable.get(ts);
if (!tab.isPartitioned()) {
if (qbParseInfo.getDestToWhereExpr().isEmpty()) {
globalLimitCtx.enableOpt(tempGlobalLimit);
}
} else {
// check if the pruner only contains partition columns
if (PartitionPruner.onlyContainsPartnCols(tab,
opToPartPruner.get(ts))) {
PrunedPartitionList partsList;
try {
String alias = (String) topOps.keySet().toArray()[0];
partsList = PartitionPruner.prune(ts, pctx, alias);
} catch (HiveException e) {
// Has to use full name to make sure it does not conflict with
// org.apache.commons.lang.StringUtils
LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
throw new SemanticException(e.getMessage(), e);
}
// If there is any unknown partition, create a map-reduce job for
// the filter to prune correctly
if (!partsList.hasUnknownPartitions()) {
globalLimitCtx.enableOpt(tempGlobalLimit);
}
}
}
if (globalLimitCtx.isEnable()) {
LOG.info("Qualify the optimize that reduces input size for 'limit' for limit "
+ globalLimitCtx.getGlobalLimit());
}
}
}
return pctx;
}
/**
* Recursively check the limit number in all sub queries
*
* @param qbParseInfo
* @return if there is one and only one limit for all subqueries, return the limit
* if there is no limit, return 0
* otherwise, return null
*/
private Integer checkQbpForGlobalLimit(QB localQb) {
QBParseInfo qbParseInfo = localQb.getParseInfo();
if (localQb.getNumSelDi() == 0 && qbParseInfo.getDestToClusterBy().isEmpty()
&& qbParseInfo.getDestToDistributeBy().isEmpty()
&& qbParseInfo.getDestToOrderBy().isEmpty()
&& qbParseInfo.getDestToSortBy().isEmpty()
&& qbParseInfo.getDestToAggregationExprs().size() <= 1
&& qbParseInfo.getDestToDistinctFuncExprs().size() <= 1
&& qbParseInfo.getNameToSample().isEmpty()) {
if ((qbParseInfo.getDestToAggregationExprs().size() < 1 ||
qbParseInfo.getDestToAggregationExprs().values().iterator().next().isEmpty()) &&
(qbParseInfo.getDestToDistinctFuncExprs().size() < 1 ||
qbParseInfo.getDestToDistinctFuncExprs().values().iterator().next().isEmpty())
&& qbParseInfo.getDestToLimit().size() <= 1) {
Integer retValue;
if (qbParseInfo.getDestToLimit().size() == 0) {
retValue = 0;
} else {
retValue = qbParseInfo.getDestToLimit().values().iterator().next();
}
for (String alias : localQb.getSubqAliases()) {
Integer limit = checkQbpForGlobalLimit(localQb.getSubqForAlias(alias).getQB());
if (limit == null) {
return null;
} else if (retValue > 0 && limit > 0) {
// Any query has more than one LIMITs shown in the query is not
// qualified to this optimization
return null;
} else if (limit > 0) {
retValue = limit;
}
}
return retValue;
}
}
return null;
}
}