[
https://issues.apache.org/jira/browse/HIVE-21382?focusedWorklogId=212608&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-212608
]
ASF GitHub Bot logged work on HIVE-21382:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 13/Mar/19 18:51
Start Date: 13/Mar/19 18:51
Worklog Time Spent: 10m
Work Description: jcamachor commented on pull request #567: HIVE-21382:
Group by keys reduction optimization - keys are not reduced in query23
URL: https://github.com/apache/hive/pull/567#discussion_r265254408
##########
File path:
ql/src/java/org/apache/hadoop/hive/ql/optimizer/calcite/rules/HiveRelFieldTrimmer.java
##########
@@ -315,48 +322,128 @@ private boolean isRexLiteral(final RexNode rexNode) {
}
+ private static class TableRefFinder extends RexVisitorImpl<Void> {
+ private Set<RexTableInputRef> tableRefs = null;
+ TableRefFinder() {
+ super(true);
+ this.tableRefs = new HashSet<>();
+ }
+
+ public Set<RexTableInputRef> getTableRefs() {
+ return this.tableRefs;
+ }
+
+ @Override
+ public Void visitTableInputRef(RexTableInputRef ref) {
+ this.tableRefs.add(ref);
+ return null;
+ }
+ }
+
// Given a groupset this tries to find out if the cardinality of the
grouping columns could have changed
// because if not and it consist of keys (unique + not null OR pk), we can
safely remove rest of the columns
// if those are columns are not being used further up
private ImmutableBitSet generateGroupSetIfCardinalitySame(final Aggregate
aggregate,
final ImmutableBitSet
originalGroupSet, final ImmutableBitSet fieldsUsed) {
- Pair<RelOptTable, List<Integer>> tabToOrgCol =
HiveRelOptUtil.getColumnOriginSet(aggregate.getInput(),
-
originalGroupSet);
- if(tabToOrgCol == null) {
- return originalGroupSet;
- }
- RelOptHiveTable tbl = (RelOptHiveTable)tabToOrgCol.left;
- List<Integer> backtrackedGBList = tabToOrgCol.right;
- ImmutableBitSet backtrackedGBSet =
ImmutableBitSet.builder().addAll(backtrackedGBList).build();
- List<ImmutableBitSet> allKeys = tbl.getNonNullableKeys();
- ImmutableBitSet currentKey = null;
- for(ImmutableBitSet key:allKeys) {
- if(backtrackedGBSet.contains(key)) {
- // only if grouping sets consist of keys
- currentKey = key;
- break;
+ RexBuilder rexBuilder = aggregate.getCluster().getRexBuilder();
+ RelMetadataQuery mq = aggregate.getCluster().getMetadataQuery();
+
+ Iterator<Integer> iterator = originalGroupSet.iterator();
+ Map<Pair<RelOptTable, Integer>, Pair<List<Integer>, List<Integer>>>
mapGBKeysLineage= new HashMap<>();
+
+ Map<Pair<RelOptTable, Integer>, List<Integer>> candidateKeys = new
HashMap<>();
+
+ while(iterator.hasNext()) {
Review comment:
```ImmutableBitSet``` implements ```implements Iterable<Integer>```, hence
we can just write ```for (int key : originalGroupSet)``` .
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Issue Time Tracking
-------------------
Worklog Id: (was: 212608)
Time Spent: 1h 20m (was: 1h 10m)
> Group by keys reduction optimization - keys are not reduced in query23
> ----------------------------------------------------------------------
>
> Key: HIVE-21382
> URL: https://issues.apache.org/jira/browse/HIVE-21382
> Project: Hive
> Issue Type: Improvement
> Reporter: Vineet Garg
> Assignee: Vineet Garg
> Priority: Major
> Labels: pull-request-available
> Attachments: HIVE-21382.1.patch, HIVE-21382.2.patch,
> HIVE-21382.2.patch, HIVE-21382.3.patch
>
> Time Spent: 1h 20m
> Remaining Estimate: 0h
>
> {code:sql}
> explain cbo with frequent_ss_items as
> (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date
> solddate,count(*) cnt
> from store_sales
> ,date_dim
> ,item
> where ss_sold_date_sk = d_date_sk
> and ss_item_sk = i_item_sk
> and d_year in (1999,1999+1,1999+2,1999+3)
> group by substr(i_item_desc,1,30),i_item_sk,d_date
> having count(*) >4)
> select sum(sales)
> from ((select cs_quantity*cs_list_price sales
> from catalog_sales
> ,date_dim
> where d_year = 1999
> and d_moy = 1
> and cs_sold_date_sk = d_date_sk
> and cs_item_sk in (select item_sk from frequent_ss_items))) subq
> limit 100;
> {code}
> {code:sql}
> HiveSortLimit(fetch=[100])
> HiveProject($f0=[$0])
> HiveAggregate(group=[{}], agg#0=[sum($0)])
> HiveProject(sales=[*(CAST($2):DECIMAL(10, 0), $3)])
> HiveSemiJoin(condition=[=($1, $5)], joinType=[inner])
> HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none],
> cost=[{2.0 rows, 0.0 cpu, 0.0 io}])
> HiveProject(cs_sold_date_sk=[$0], cs_item_sk=[$15],
> cs_quantity=[$18], cs_list_price=[$20])
> HiveFilter(condition=[IS NOT NULL($0)])
> HiveTableScan(table=[[perf_constraints, catalog_sales]],
> table:alias=[catalog_sales])
> HiveProject(d_date_sk=[$0])
> HiveFilter(condition=[AND(=($6, 1999), =($8, 1))])
> HiveTableScan(table=[[perf_constraints, date_dim]],
> table:alias=[date_dim])
> HiveProject(i_item_sk=[$1])
> HiveFilter(condition=[>($3, 4)])
> HiveProject(substr=[$2], i_item_sk=[$1], d_date=[$0], $f3=[$3])
> HiveAggregate(group=[{3, 4, 5}], agg#0=[count()])
> HiveJoin(condition=[=($1, $4)], joinType=[inner],
> algorithm=[none], cost=[{2.0 rows, 0.0 cpu, 0.0 io}])
> HiveJoin(condition=[=($0, $2)], joinType=[inner],
> algorithm=[none], cost=[{2.0 rows, 0.0 cpu, 0.0 io}])
> HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2])
> HiveFilter(condition=[IS NOT NULL($0)])
> HiveTableScan(table=[[perf_constraints,
> store_sales]], table:alias=[store_sales])
> HiveProject(d_date_sk=[$0], d_date=[$2])
> HiveFilter(condition=[IN($6, 1999, 2000, 2001, 2002)])
> HiveTableScan(table=[[perf_constraints, date_dim]],
> table:alias=[date_dim])
> HiveProject(i_item_sk=[$0], substr=[substr($4, 1, 30)])
> HiveTableScan(table=[[perf_constraints, item]],
> table:alias=[item])
> {code}
> Right side of HiveSemiJoin has an aggregate which could be reduce to have
> only {{i_item_sk}} as group by key since {{i_item_sk}} is primary key.
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