Boaz Ben-Zvi created DRILL-6735:
-----------------------------------
Summary: Enhance the Hash-Join Operator to perform Semi and
Anti-Semi joins
Key: DRILL-6735
URL: https://issues.apache.org/jira/browse/DRILL-6735
Project: Apache Drill
Issue Type: Improvement
Components: Execution - Relational Operators, Query Planning &
Optimization
Affects Versions: 1.14.0
Reporter: Boaz Ben-Zvi
Assignee: Boaz Ben-Zvi
Fix For: 1.15.0
Currently Drill implements Semi-Join (see DRILL-402) by using a regular join,
with a DISTINCT operator under the build upstream side to eliminate duplicates.
Typically a physical plan for the Semi uses a hash-join, with a hash-aggr
performing the DISTINCT (see example below).
This effectively builds the same hash table(s) twice - a big waste of time
and memory.
+Improvement+: Eliminate the Hash-Aggr from the plan, and notify the Hash-Join
to perform a Semi-join. The HJ then would just skip the duplicates in its hash
table(s), thus performing a Semi -Join.
Example:
{code}
select c.c_first_name, c.c_last_name from dfs.`/data/json/s1/customer` c where
c.c_customer_sk in (select s.ss_customer_sk from
dfs.`/data/json/s1/store_sales` s) limit 4;
{code}
And the result plan (see the HJ at 01-03, and the Hash Agg at 01-05):
{code}
00-00 Screen : rowType = RecordType(ANY c_first_name, ANY c_last_name):
rowcount = 4.0, cumulative cost = {4693752.96 rows, 2.3095576720000003E7 cpu,
0.0 io, 2.1598011392E9 network, 3.5895861760000005E7 memory}, id = 1320
00-01 Project(c_first_name=[$1], c_last_name=[$2]) : rowType =
RecordType(ANY c_first_name, ANY c_last_name): rowcount = 4.0, cumulative cost
= {4693752.56 rows, 2.3095576320000004E7 cpu, 0.0 io, 2.1598011392E9 network,
3.5895861760000005E7 memory}, id = 1319
00-02 Project(c_customer_sk=[$1], c_first_name=[$2], c_last_name=[$3],
ss_customer_sk=[$0]) : rowType = RecordType(ANY c_customer_sk, ANY
c_first_name, ANY c_last_name, ANY ss_customer_sk): rowcount = 4.0, cumulative
cost = {4693748.56 rows, 2.3095568320000004E7 cpu, 0.0 io, 2.1598011392E9
network, 3.5895861760000005E7 memory}, id = 1318
00-03 SelectionVectorRemover : rowType = RecordType(ANY
ss_customer_sk, ANY c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount
= 4.0, cumulative cost = {4693744.56 rows, 2.3095552320000004E7 cpu, 0.0 io,
2.1598011392E9 network, 3.5895861760000005E7 memory}, id = 1317
00-04 Limit(fetch=[4]) : rowType = RecordType(ANY ss_customer_sk,
ANY c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount = 4.0,
cumulative cost = {4693740.56 rows, 2.3095548320000004E7 cpu, 0.0 io,
2.1598011392E9 network, 3.5895861760000005E7 memory}, id = 1316
00-05 UnionExchange : rowType = RecordType(ANY ss_customer_sk, ANY
c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount = 4.0, cumulative
cost = {4693736.56 rows, 2.3095532320000004E7 cpu, 0.0 io, 2.1598011392E9
network, 3.5895861760000005E7 memory}, id = 1315
01-01 SelectionVectorRemover : rowType = RecordType(ANY
ss_customer_sk, ANY c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount
= 4.0, cumulative cost = {4693732.56 rows, 2.3095500320000004E7 cpu, 0.0 io,
2.1597356032E9 network, 3.5895861760000005E7 memory}, id = 1314
01-02 Limit(fetch=[4]) : rowType = RecordType(ANY
ss_customer_sk, ANY c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount
= 4.0, cumulative cost = {4693728.56 rows, 2.3095496320000004E7 cpu, 0.0 io,
2.1597356032E9 network, 3.5895861760000005E7 memory}, id = 1313
01-03 HashJoin(condition=[=($1, $0)], joinType=[inner]) :
rowType = RecordType(ANY ss_customer_sk, ANY c_customer_sk, ANY c_first_name,
ANY c_last_name): rowcount = 90182.8, cumulative cost = {4693724.56 rows,
2.3095480320000004E7 cpu, 0.0 io, 2.1597356032E9 network, 3.5895861760000005E7
memory}, id = 1312
01-05 HashAgg(group=[{0}]) : rowType = RecordType(ANY
ss_customer_sk): rowcount = 18036.56, cumulative cost = {4509140.0 rows,
2.1824237600000005E7 cpu, 0.0 io, 1.4775549952E9 network, 3.4918780160000004E7
memory}, id = 1309
01-06 Project(ss_customer_sk=[$0]) : rowType =
RecordType(ANY ss_customer_sk): rowcount = 180365.6, cumulative cost =
{4328774.4 rows, 2.0381312800000004E7 cpu, 0.0 io, 1.4775549952E9 network,
3.17443456E7 memory}, id = 1308
01-07 HashToRandomExchange(dist0=[[$0]]) : rowType =
RecordType(ANY ss_customer_sk, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount =
180365.6, cumulative cost = {4148408.8000000003 rows, 2.0200947200000003E7 cpu,
0.0 io, 1.4775549952E9 network, 3.17443456E7 memory}, id = 1307
02-01 UnorderedMuxExchange : rowType =
RecordType(ANY ss_customer_sk, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount =
180365.6, cumulative cost = {3968043.2 rows, 1.73150976E7 cpu, 0.0 io, 0.0
network, 3.17443456E7 memory}, id = 1306
04-01 Project(ss_customer_sk=[$0],
E_X_P_R_H_A_S_H_F_I_E_L_D=[hash32AsDouble($0, 1301011)]) : rowType =
RecordType(ANY ss_customer_sk, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount =
180365.6, cumulative cost = {3787677.6 rows, 1.7134732E7 cpu, 0.0 io, 0.0
network, 3.17443456E7 memory}, id = 1305
04-02 HashAgg(group=[{0}]) : rowType =
RecordType(ANY ss_customer_sk): rowcount = 180365.6, cumulative cost =
{3607312.0 rows, 1.6232904E7 cpu, 0.0 io, 0.0 network, 3.17443456E7 memory}, id
= 1304
04-03 Scan(groupscan=[EasyGroupScan
[selectionRoot=file:/data/json/s1/store_sales, numFiles=1,
columns=[`ss_customer_sk`],
files=[file:/data/json/s1/store_sales/0_0_0.json]]]) : rowType = RecordType(ANY
ss_customer_sk): rowcount = 1803656.0, cumulative cost = {1803656.0 rows,
1803656.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 1303
01-04 BroadcastExchange : rowType = RecordType(ANY
c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount = 55516.0,
cumulative cost = {111032.0 rows, 610676.0 cpu, 0.0 io, 6.82180608E8 network,
0.0 memory}, id = 1311
03-01 Scan(groupscan=[EasyGroupScan
[selectionRoot=file:/data/json/s1/customer, numFiles=1,
columns=[`c_customer_sk`, `c_first_name`, `c_last_name`],
files=[file:/data/json/s1/customer/0_0_0.json]]]) : rowType = RecordType(ANY
c_customer_sk, ANY c_first_name, ANY c_last_name): rowcount = 55516.0,
cumulative cost = {55516.0 rows, 166548.0 cpu, 0.0 io, 0.0 network, 0.0
memory}, id = 1310
{code}
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