GitHub user kiszk opened a pull request:
https://github.com/apache/spark/pull/11636
[SPARK-13805][SQL] Generate code that get a value in each column from
ColumnVector when ColumnarVector is used
## What changes were proposed in this pull request?
This PR generates code that get a value in each column from
```ColumnVector``` instead of creating ```InternalRow``` when
```ColumnarBatch``` is accessed. This PR improves benchmark program by up to
15%.
This PR consists of two parts:
1. Get an ```ColumnVector ``` by using ```ColumnarBatch.column()``` method
2. Get a value of each column by using
```rdd_col${COLIDX}.getInt(ROWIDX)``` instead of ```rdd_row.getInt(COLIDX)```
This is a motivated example.
````
sqlContext.conf.setConfString(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key,
"true")
sqlContext.conf.setConfString(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key,
"true")
val values = 10
withTempPath { dir =>
withTempTable("t1", "tempTable") {
sqlContext.range(values).registerTempTable("t1")
sqlContext.sql("select id % 2 as p, cast(id as INT) as id from t1")
.write.partitionBy("p").parquet(dir.getCanonicalPath)
sqlContext.read.parquet(dir.getCanonicalPath).registerTempTable("tempTable")
sqlContext.sql("select sum(p) from tempTable").collect
}
}
````
The original code
````
...
/* 072 */ while (!shouldStop() && rdd_batchIdx < numRows) {
/* 073 */ InternalRow rdd_row =
rdd_batch.getRow(rdd_batchIdx++);
/* 074 */ /*** CONSUME: TungstenAggregate(key=[],
functions=[(sum(cast(p#4 as bigint)),mode=Partial,isDistinct=false)],
output=[sum#10L]) */
/* 075 */ /* input[0, int] */
/* 076 */ boolean rdd_isNull = rdd_row.isNullAt(0);
/* 077 */ int rdd_value = rdd_isNull ? -1 : (rdd_row.getInt(0));
...
````
The code generated by this PR
````
/* 072 */ while (!shouldStop() && rdd_batchIdx < numRows) {
/* 073 */
org.apache.spark.sql.execution.vectorized.ColumnVector rdd_col0 =
rdd_batch.column(0);
/* 074 */ /*** CONSUME: TungstenAggregate(key=[],
functions=[(sum(cast(p#4 as bigint)),mode=Partial,isDistinct=false)],
output=[sum#10L]) */
/* 075 */ /* input[0, int] */
/* 076 */ boolean rdd_isNull = rdd_col0.getIsNull(rdd_batchIdx);
/* 077 */ int rdd_value = rdd_isNull ? -1 :
(rdd_col0.getInt(rdd_batchIdx));
...
/* 128 */ rdd_batchIdx++;
/* 129 */ }
/* 130 */ if (shouldStop()) return;
````
Performance
Without this PR
````
model name : Intel(R) Xeon(R) CPU E5-2667 v2 @ 3.30GHz
Partitioned Table: Best/Avg Time(ms) Rate(M/s) Per
Row(ns) Relative
-------------------------------------------------------------------------------------------
Read data column 434 / 488 36.3
27.6 1.0X
Read partition column 302 / 346 52.1
19.2 1.4X
Read both columns 588 / 643 26.8
37.4 0.7X
````
With this PR
````
model name : Intel(R) Xeon(R) CPU E5-2667 v2 @ 3.30GHz
Partitioned Table: Best/Avg Time(ms) Rate(M/s) Per
Row(ns) Relative
-------------------------------------------------------------------------------------------
Read data column 392 / 516 40.1
24.9 1.0X
Read partition column 256 / 318 61.4
16.3 1.5X
Read both columns 523 / 539 30.1
33.3 0.7X
````
## How was this patch tested?
Tested by existing test suites and benchmark
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/kiszk/spark SPARK-13805
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/11636.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #11636
----
commit 0db679f9bdc410cd7483faa366557cc5e5925889
Author: Kazuaki Ishizaki <ishiz...@jp.ibm.com>
Date: 2016-03-10T19:15:05Z
Generate code that get a value in each column from ColumnVector when
ColumnarVector is used
----
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