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https://issues.apache.org/jira/browse/PHOENIX-3670?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15865978#comment-15865978
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chenglei edited comment on PHOENIX-3670 at 2/14/17 3:44 PM:
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I uploaded my first patch, could someone help me review for this patch? The
time complexity of KeyRange.intersect method in my patch is reduced to
O(M*logM)+O(N*logN), which is faster than current O(M*N) ,and for my example
explained above,after applied the patch,KeyRange.intersect method only cost
20ms, dramatically faster than original 11s.
I also add some unit tests for KeyRange.intersect(List,List) method in my patch.
was (Author: comnetwork):
I uploaded my first patch, could someone help me review for this patch? The
time complexity of KeyRange.intersect method in my patch is reduced to
O(M*logM)+O(N*logN), which is faster than current O(M*N) ,and for my example
explained above,after applied the patch,KeyRange.intersect method only cost
20ms, dramatically faster than original 11s.I also add some unit tests for
KeyRange.intersect(List,List) method in my patch.
> KeyRange.intersect(List<KeyRange> , List<KeyRange>) is inefficient,especially
> for join dynamic filter
> -----------------------------------------------------------------------------------------------------
>
> Key: PHOENIX-3670
> URL: https://issues.apache.org/jira/browse/PHOENIX-3670
> Project: Phoenix
> Issue Type: Improvement
> Affects Versions: 4.9.0
> Reporter: chenglei
> Attachments: PHOENIX-3670_v1.patch
>
>
> In my business system, there is a following join SQL(which is simplified),
> fact_table is a fact table, joining dimension table dim_table1 and
> dim_table2 :
> {code:borderStyle=solid}
> select /*+ SKIP_SCAN */ sum(t.click) from fact_table t join dim_table1 d1 on
> t.cust_id=d1.id join dim_table2 d2 on t.cust_id =d2.id where t.date
> between '2016-01-01' and '2017-01-01' and d1.code = 2008 and d2.region = 'us';
> {code}
> I use /*+ SKIP_SCAN */ hint to enable join dynamic filter. For some small
> dataset, the sql executes quickly, but when the dataset is bigger, the sql
> become very slowly. When the row count of fact_table is 30
> million,dim_table1 is 300 thousand and dim_table2 is 100 thousand, the above
> query costs 17s.
> When I debug the SQL executing, I find RHS1 return 5523 rows:
> {code:borderStyle=solid}
> select d1.id from dim_table1 d1 where d1.code = 2008
> {code}
> and RHS2 return 23881 rows:
> {code:borderStyle=solid}
> select d2.id from dim_table2 d2 where d2.region='us'
> {code}
> then HashJoinPlan uses KeyRange.intersect(List<KeyRange> , List<KeyRange> )
> method to compute RHS1 intersecting RHS2 for dynamic filter, narrowing down
> fact_table.cust_id should be.
> Surprisingly,the KeyRange.intersect method costs 11s ! although the whole sql
> execution only costs 17s.After I read the code of KeyRange.intersect
> method,I find following two problem:
> 1. The double loop is inefficient in line 521 and line 522,when keyRanges
> size is M, keyRanges2 size is N, the time complexity is O(M*N), for my
> example,is 5523*23881:
> {code:borderStyle=solid}
> 519 public static List<KeyRange> intersect(List<KeyRange> keyRanges,
> List<KeyRange> keyRanges2) {
> 520 List<KeyRange> tmp = new ArrayList<KeyRange>();
> 521 for (KeyRange r1 : keyRanges) {
> 522 for (KeyRange r2 : keyRanges2) {
> 523 KeyRange r = r1.intersect(r2);
> 524 if (EMPTY_RANGE != r) {
> 525 tmp.add(r);
> 526 }
> 527 }
> 528 }
> {code}
> 2. line 540 shoule be r = r.union(tmp.get( i )), not intersect, just as
> KeyRange.coalesce method does:
> {code:borderStyle=solid}
> 532 Collections.sort(tmp, KeyRange.COMPARATOR);
> 533 List<KeyRange> tmp2 = new ArrayList<KeyRange>();
> 534 KeyRange r = tmp.get(0);
> 535 for (int i=1; i<tmp.size(); i++) {
> 536 if (EMPTY_RANGE == r.intersect(tmp.get(i))) {
> 537 tmp2.add(r);
> 538 r = tmp.get(i);
> 539 } else {
> 540 r = r.intersect(tmp.get(i));
> 541 }
> 542 }
> {code}
> and it seems that no unit tests for KeyRange.intersect(List<KeyRange> ,
> List<KeyRange>) method.
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