ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Kazuaki Ishizaki c235b5f977 [SPARK-22746][SQL] Avoid the generation of useless mutable states by SortMergeJoin 
## What changes were proposed in this pull request?

This PR reduce the number of global mutable variables in generated code of `SortMergeJoin`.

Before this PR, global mutable variables are used to extend lifetime of variables in the nested loop. This can be achieved by declaring variable at the outer most loop level where the variables are used.
In the following example, `smj_value8`, `smj_value8`, and `smj_value9` are declared as local variable at lines 145-147 in `With this PR`.

This PR fixes potential assertion error by #19865. Without this PR, a global mutable variable is potentially passed to arguments in generated code of split function.

Without this PR
```
/* 010 */   int smj_value8;
/* 011 */   boolean smj_value8;
/* 012 */   int smj_value9;
..
/* 143 */   protected void processNext() throws java.io.IOException {
/* 144 */     while (findNextInnerJoinRows(smj_leftInput, smj_rightInput)) {
/* 145 */       boolean smj_loaded = false;
/* 146 */       smj_isNull6 = smj_leftRow.isNullAt(1);
/* 147 */       smj_value9 = smj_isNull6 ? -1 : (smj_leftRow.getInt(1));
/* 148 */       scala.collection.Iterator<UnsafeRow> smj_iterator = smj_matches.generateIterator();
/* 149 */       while (smj_iterator.hasNext()) {
/* 150 */         InternalRow smj_rightRow1 = (InternalRow) smj_iterator.next();
/* 151 */         boolean smj_isNull8 = smj_rightRow1.isNullAt(1);
/* 152 */         int smj_value11 = smj_isNull8 ? -1 : (smj_rightRow1.getInt(1));
/* 153 */
/* 154 */         boolean smj_value12 = (smj_isNull6 && smj_isNull8) ||
/* 155 */         (!smj_isNull6 && !smj_isNull8 && smj_value9 == smj_value11);
/* 156 */         if (false || !smj_value12) continue;
/* 157 */         if (!smj_loaded) {
/* 158 */           smj_loaded = true;
/* 159 */           smj_value8 = smj_leftRow.getInt(0);
/* 160 */         }
/* 161 */         int smj_value10 = smj_rightRow1.getInt(0);
/* 162 */         smj_numOutputRows.add(1);
/* 163 */
/* 164 */         smj_rowWriter.zeroOutNullBytes();
/* 165 */
/* 166 */         smj_rowWriter.write(0, smj_value8);
/* 167 */
/* 168 */         if (smj_isNull6) {
/* 169 */           smj_rowWriter.setNullAt(1);
/* 170 */         } else {
/* 171 */           smj_rowWriter.write(1, smj_value9);
/* 172 */         }
/* 173 */
/* 174 */         smj_rowWriter.write(2, smj_value10);
/* 175 */
/* 176 */         if (smj_isNull8) {
/* 177 */           smj_rowWriter.setNullAt(3);
/* 178 */         } else {
/* 179 */           smj_rowWriter.write(3, smj_value11);
/* 180 */         }
/* 181 */         append(smj_result.copy());
/* 182 */
/* 183 */       }
/* 184 */       if (shouldStop()) return;
/* 185 */     }
/* 186 */   }
```

With this PR
```
/* 143 */   protected void processNext() throws java.io.IOException {
/* 144 */     while (findNextInnerJoinRows(smj_leftInput, smj_rightInput)) {
/* 145 */       int smj_value8 = -1;
/* 146 */       boolean smj_isNull6 = false;
/* 147 */       int smj_value9 = -1;
/* 148 */       boolean smj_loaded = false;
/* 149 */       smj_isNull6 = smj_leftRow.isNullAt(1);
/* 150 */       smj_value9 = smj_isNull6 ? -1 : (smj_leftRow.getInt(1));
/* 151 */       scala.collection.Iterator<UnsafeRow> smj_iterator = smj_matches.generateIterator();
/* 152 */       while (smj_iterator.hasNext()) {
/* 153 */         InternalRow smj_rightRow1 = (InternalRow) smj_iterator.next();
/* 154 */         boolean smj_isNull8 = smj_rightRow1.isNullAt(1);
/* 155 */         int smj_value11 = smj_isNull8 ? -1 : (smj_rightRow1.getInt(1));
/* 156 */
/* 157 */         boolean smj_value12 = (smj_isNull6 && smj_isNull8) ||
/* 158 */         (!smj_isNull6 && !smj_isNull8 && smj_value9 == smj_value11);
/* 159 */         if (false || !smj_value12) continue;
/* 160 */         if (!smj_loaded) {
/* 161 */           smj_loaded = true;
/* 162 */           smj_value8 = smj_leftRow.getInt(0);
/* 163 */         }
/* 164 */         int smj_value10 = smj_rightRow1.getInt(0);
/* 165 */         smj_numOutputRows.add(1);
/* 166 */
/* 167 */         smj_rowWriter.zeroOutNullBytes();
/* 168 */
/* 169 */         smj_rowWriter.write(0, smj_value8);
/* 170 */
/* 171 */         if (smj_isNull6) {
/* 172 */           smj_rowWriter.setNullAt(1);
/* 173 */         } else {
/* 174 */           smj_rowWriter.write(1, smj_value9);
/* 175 */         }
/* 176 */
/* 177 */         smj_rowWriter.write(2, smj_value10);
/* 178 */
/* 179 */         if (smj_isNull8) {
/* 180 */           smj_rowWriter.setNullAt(3);
/* 181 */         } else {
/* 182 */           smj_rowWriter.write(3, smj_value11);
/* 183 */         }
/* 184 */         append(smj_result.copy());
/* 185 */
/* 186 */       }
/* 187 */       if (shouldStop()) return;
/* 188 */     }
/* 189 */   }
```

## How was this patch tested?

Existing test cases

Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>

Closes #19937 from kiszk/SPARK-22746.
2017-12-11 13:15:45 -08:00
..
catalyst [SPARK-12297][SQL] Adjust timezone for int96 data from impala 2017-12-09 11:53:15 +09:00
core [SPARK-22746][SQL] Avoid the generation of useless mutable states by SortMergeJoin 2017-12-11 13:15:45 -08:00
hive [SPARK-22642][SQL] the createdTempDir will not be deleted if an exception occurs, should delete it with try-finally. 2017-12-11 13:36:15 -06:00
hive-thriftserver Revert "[SPARK-22496][SQL] thrift server adds operation logs" 2017-12-11 13:08:42 -08:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00

README.md

Spark SQL

This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.

Spark SQL is broken up into four subprojects:

  • Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
  • Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
  • Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
  • HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.