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authorKazuaki Ishizaki <ishizaki@jp.ibm.com>2016-12-29 10:59:37 +0800
committerWenchen Fan <wenchen@databricks.com>2016-12-29 10:59:37 +0800
commit93f35569fd4e7dc1e4037d3df538a21c526f9c5d (patch)
tree0b2c59ed90ca9ae1ccb33a3956ac5a69dcdd344e /sql/core
parent092c6725bf039bf33299b53791e1958c4ea3f6aa (diff)
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[SPARK-16213][SQL] Reduce runtime overhead of a program that creates an primitive array in DataFrame
## What changes were proposed in this pull request? This PR reduces runtime overhead of a program the creates an primitive array in DataFrame by using the similar approach to #15044. Generated code performs boxing operation in an assignment from InternalRow to an `Object[]` temporary array (at Lines 051 and 061 in the generated code before without this PR). If we know that type of array elements is primitive, we apply the following optimizations: 1. Eliminate a pair of `isNullAt()` and a null assignment 2. Allocate an primitive array instead of `Object[]` (eliminate boxing operations) 3. Create `UnsafeArrayData` by using `UnsafeArrayWriter` to keep a primitive array in a row format instead of doing non-lightweight operations in constructor of `GenericArrayData` The PR also performs the same things for `CreateMap`. Here are performance results of [DataFrame programs](https://github.com/kiszk/spark/blob/6bf54ec5e227689d69f6db991e9ecbc54e153d0a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/PrimitiveArrayBenchmark.scala#L83-L112) by up to 17.9x over without this PR. ``` Without SPARK-16043 OpenJDK 64-Bit Server VM 1.8.0_91-b14 on Linux 4.4.11-200.fc22.x86_64 Intel Xeon E3-12xx v2 (Ivy Bridge) Read a primitive array in DataFrame: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ Int 3805 / 4150 0.0 507308.9 1.0X Double 3593 / 3852 0.0 479056.9 1.1X With SPARK-16043 Read a primitive array in DataFrame: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ Int 213 / 271 0.0 28387.5 1.0X Double 204 / 223 0.0 27250.9 1.0X ``` Note : #15780 is enabled for these measurements An motivating example ``` java val df = sparkContext.parallelize(Seq(0.0d, 1.0d), 1).toDF df.selectExpr("Array(value + 1.1d, value + 2.2d)").show ``` Generated code without this PR ``` java /* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator { /* 006 */ private Object[] references; /* 007 */ private scala.collection.Iterator[] inputs; /* 008 */ private scala.collection.Iterator inputadapter_input; /* 009 */ private UnsafeRow serializefromobject_result; /* 010 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder serializefromobject_holder; /* 011 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter serializefromobject_rowWriter; /* 012 */ private Object[] project_values; /* 013 */ private UnsafeRow project_result; /* 014 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder project_holder; /* 015 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter project_rowWriter; /* 016 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter project_arrayWriter; /* 017 */ /* 018 */ public GeneratedIterator(Object[] references) { /* 019 */ this.references = references; /* 020 */ } /* 021 */ /* 022 */ public void init(int index, scala.collection.Iterator[] inputs) { /* 023 */ partitionIndex = index; /* 024 */ this.inputs = inputs; /* 025 */ inputadapter_input = inputs[0]; /* 026 */ serializefromobject_result = new UnsafeRow(1); /* 027 */ this.serializefromobject_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(serializefromobject_result, 0); /* 028 */ this.serializefromobject_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(serializefromobject_holder, 1); /* 029 */ this.project_values = null; /* 030 */ project_result = new UnsafeRow(1); /* 031 */ this.project_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(project_result, 32); /* 032 */ this.project_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(project_holder, 1); /* 033 */ this.project_arrayWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter(); /* 034 */ /* 035 */ } /* 036 */ /* 037 */ protected void processNext() throws java.io.IOException { /* 038 */ while (inputadapter_input.hasNext()) { /* 039 */ InternalRow inputadapter_row = (InternalRow) inputadapter_input.next(); /* 040 */ double inputadapter_value = inputadapter_row.getDouble(0); /* 041 */ /* 042 */ final boolean project_isNull = false; /* 043 */ this.project_values = new Object[2]; /* 044 */ boolean project_isNull1 = false; /* 045 */ /* 046 */ double project_value1 = -1.0; /* 047 */ project_value1 = inputadapter_value + 1.1D; /* 048 */ if (false) { /* 049 */ project_values[0] = null; /* 050 */ } else { /* 051 */ project_values[0] = project_value1; /* 052 */ } /* 053 */ /* 054 */ boolean project_isNull4 = false; /* 055 */ /* 056 */ double project_value4 = -1.0; /* 057 */ project_value4 = inputadapter_value + 2.2D; /* 058 */ if (false) { /* 059 */ project_values[1] = null; /* 060 */ } else { /* 061 */ project_values[1] = project_value4; /* 062 */ } /* 063 */ /* 064 */ final ArrayData project_value = new org.apache.spark.sql.catalyst.util.GenericArrayData(project_values); /* 065 */ this.project_values = null; /* 066 */ project_holder.reset(); /* 067 */ /* 068 */ project_rowWriter.zeroOutNullBytes(); /* 069 */ /* 070 */ if (project_isNull) { /* 071 */ project_rowWriter.setNullAt(0); /* 072 */ } else { /* 073 */ // Remember the current cursor so that we can calculate how many bytes are /* 074 */ // written later. /* 075 */ final int project_tmpCursor = project_holder.cursor; /* 076 */ /* 077 */ if (project_value instanceof UnsafeArrayData) { /* 078 */ final int project_sizeInBytes = ((UnsafeArrayData) project_value).getSizeInBytes(); /* 079 */ // grow the global buffer before writing data. /* 080 */ project_holder.grow(project_sizeInBytes); /* 081 */ ((UnsafeArrayData) project_value).writeToMemory(project_holder.buffer, project_holder.cursor); /* 082 */ project_holder.cursor += project_sizeInBytes; /* 083 */ /* 084 */ } else { /* 085 */ final int project_numElements = project_value.numElements(); /* 086 */ project_arrayWriter.initialize(project_holder, project_numElements, 8); /* 087 */ /* 088 */ for (int project_index = 0; project_index < project_numElements; project_index++) { /* 089 */ if (project_value.isNullAt(project_index)) { /* 090 */ project_arrayWriter.setNullDouble(project_index); /* 091 */ } else { /* 092 */ final double project_element = project_value.getDouble(project_index); /* 093 */ project_arrayWriter.write(project_index, project_element); /* 094 */ } /* 095 */ } /* 096 */ } /* 097 */ /* 098 */ project_rowWriter.setOffsetAndSize(0, project_tmpCursor, project_holder.cursor - project_tmpCursor); /* 099 */ } /* 100 */ project_result.setTotalSize(project_holder.totalSize()); /* 101 */ append(project_result); /* 102 */ if (shouldStop()) return; /* 103 */ } /* 104 */ } /* 105 */ } ``` Generated code with this PR ``` java /* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator { /* 006 */ private Object[] references; /* 007 */ private scala.collection.Iterator[] inputs; /* 008 */ private scala.collection.Iterator inputadapter_input; /* 009 */ private UnsafeRow serializefromobject_result; /* 010 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder serializefromobject_holder; /* 011 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter serializefromobject_rowWriter; /* 012 */ private UnsafeArrayData project_arrayData; /* 013 */ private UnsafeRow project_result; /* 014 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder project_holder; /* 015 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter project_rowWriter; /* 016 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter project_arrayWriter; /* 017 */ /* 018 */ public GeneratedIterator(Object[] references) { /* 019 */ this.references = references; /* 020 */ } /* 021 */ /* 022 */ public void init(int index, scala.collection.Iterator[] inputs) { /* 023 */ partitionIndex = index; /* 024 */ this.inputs = inputs; /* 025 */ inputadapter_input = inputs[0]; /* 026 */ serializefromobject_result = new UnsafeRow(1); /* 027 */ this.serializefromobject_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(serializefromobject_result, 0); /* 028 */ this.serializefromobject_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(serializefromobject_holder, 1); /* 029 */ /* 030 */ project_result = new UnsafeRow(1); /* 031 */ this.project_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(project_result, 32); /* 032 */ this.project_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(project_holder, 1); /* 033 */ this.project_arrayWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter(); /* 034 */ /* 035 */ } /* 036 */ /* 037 */ protected void processNext() throws java.io.IOException { /* 038 */ while (inputadapter_input.hasNext()) { /* 039 */ InternalRow inputadapter_row = (InternalRow) inputadapter_input.next(); /* 040 */ double inputadapter_value = inputadapter_row.getDouble(0); /* 041 */ /* 042 */ byte[] project_array = new byte[32]; /* 043 */ project_arrayData = new UnsafeArrayData(); /* 044 */ Platform.putLong(project_array, 16, 2); /* 045 */ project_arrayData.pointTo(project_array, 16, 32); /* 046 */ /* 047 */ boolean project_isNull1 = false; /* 048 */ /* 049 */ double project_value1 = -1.0; /* 050 */ project_value1 = inputadapter_value + 1.1D; /* 051 */ if (false) { /* 052 */ project_arrayData.setNullAt(0); /* 053 */ } else { /* 054 */ project_arrayData.setDouble(0, project_value1); /* 055 */ } /* 056 */ /* 057 */ boolean project_isNull4 = false; /* 058 */ /* 059 */ double project_value4 = -1.0; /* 060 */ project_value4 = inputadapter_value + 2.2D; /* 061 */ if (false) { /* 062 */ project_arrayData.setNullAt(1); /* 063 */ } else { /* 064 */ project_arrayData.setDouble(1, project_value4); /* 065 */ } /* 066 */ project_holder.reset(); /* 067 */ /* 068 */ // Remember the current cursor so that we can calculate how many bytes are /* 069 */ // written later. /* 070 */ final int project_tmpCursor = project_holder.cursor; /* 071 */ /* 072 */ if (project_arrayData instanceof UnsafeArrayData) { /* 073 */ final int project_sizeInBytes = ((UnsafeArrayData) project_arrayData).getSizeInBytes(); /* 074 */ // grow the global buffer before writing data. /* 075 */ project_holder.grow(project_sizeInBytes); /* 076 */ ((UnsafeArrayData) project_arrayData).writeToMemory(project_holder.buffer, project_holder.cursor); /* 077 */ project_holder.cursor += project_sizeInBytes; /* 078 */ /* 079 */ } else { /* 080 */ final int project_numElements = project_arrayData.numElements(); /* 081 */ project_arrayWriter.initialize(project_holder, project_numElements, 8); /* 082 */ /* 083 */ for (int project_index = 0; project_index < project_numElements; project_index++) { /* 084 */ if (project_arrayData.isNullAt(project_index)) { /* 085 */ project_arrayWriter.setNullDouble(project_index); /* 086 */ } else { /* 087 */ final double project_element = project_arrayData.getDouble(project_index); /* 088 */ project_arrayWriter.write(project_index, project_element); /* 089 */ } /* 090 */ } /* 091 */ } /* 092 */ /* 093 */ project_rowWriter.setOffsetAndSize(0, project_tmpCursor, project_holder.cursor - project_tmpCursor); /* 094 */ project_result.setTotalSize(project_holder.totalSize()); /* 095 */ append(project_result); /* 096 */ if (shouldStop()) return; /* 097 */ } /* 098 */ } /* 099 */ } ``` ## How was this patch tested? Added unit tests into `DataFrameComplexTypeSuite` Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com> Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #13909 from kiszk/SPARK-16213.
Diffstat (limited to 'sql/core')
-rw-r--r--sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVector.java6
1 files changed, 6 insertions, 0 deletions
diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVector.java b/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVector.java
index ff07940422..354c878aca 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVector.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVector.java
@@ -246,6 +246,12 @@ public abstract class ColumnVector implements AutoCloseable {
public Object get(int ordinal, DataType dataType) {
throw new UnsupportedOperationException();
}
+
+ @Override
+ public void update(int ordinal, Object value) { throw new UnsupportedOperationException(); }
+
+ @Override
+ public void setNullAt(int ordinal) { throw new UnsupportedOperationException(); }
}
/**