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 ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org