[SPARK-16844][SQL] Generate code for sort based aggregation by yucai · Pull Request #14481 · apache/spark

yucai · 2016-08-03T15:16:12Z

This PR is in internal review and will ask for community review later.

hvanhovell · 2016-08-03T19:29:11Z

Ok to test

SparkQA · 2016-08-04T09:55:56Z

Test build #3202 has finished for PR 14481 at commit dc0f040.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

yucai · 2016-08-15T03:15:19Z

retest this please

hvanhovell · 2016-08-15T15:45:29Z

@yucai could you post some benchmark results? I would think that the overall runtime of the sort based aggregation path is dominated by the preceding exchange and sort operations, and that as a result this will not yield a enormous speed-up.

Could you also post the generated code for a simple case? The helps during the review.

yucai · 2016-08-16T01:14:00Z

@hvanhovell thanks very much for the advice, yes, I will post the benchmark results first.
And it is WIP, I will post a generated codes, but kindly not review the codes details at present, I am pretty sure some place could be improved :).

yucai · 2016-08-17T13:14:00Z

@hvanhovell
Benchmark Result

Summary
We benchmark sortagg code gen with real custormers cases, and it improves x6 when aggregating without keys, improves x1.18 when aggregating with keys.

Workload
Example 1: aggregate without keys

SELECT
mbuser_id, max(substr(acc_nbr,1,15)) acc_nbr, max(nbilling_tid) NBILLING_TID, max(obilling_tid) OBILLING_TID, max(BRAND_ID) BRAND_ID, max(tm_tid) tm_tid, max(area_id) AREA_ID, max(VPMN_ID) VPMN_ID, max(ACCT_ID) ACCT_ID, ….
FROM gdi_mb GROUP BY MbUser_ID;

Example 2: aggregate with keys

SELECT
max(substr(acc_nbr,1,15)) acc_nbr, max(nbilling_tid) NBILLING_TID, max(obilling_tid) OBILLING_TID, max(BRAND_ID) BRAND_ID, max(tm_tid) tm_tid, max(area_id) AREA_ID, max(VPMN_ID) VPMN_ID, max(ACCT_ID) ACCT_ID, ….
FROM gdi_mb;

Report (in seconds)

In above workload pattern, sort actually occpies few time, most of time is used in aggregation, that's the main reason why sortagg code gen speeds up.

yucai · 2016-08-17T13:17:13Z

Generated code example, not for code review yet

scala> Seq(("a", "3"), ("b", "20"), ("b", "2")).toDF("k", "v").agg(max("v")).debugCodegen()
Found 2 WholeStageCodegen subtrees.
== Subtree 1 / 2 ==
*SortAggregate(key=[], functions=[partial_max(v#6)], output=[max#18])
+- LocalTableScan [v#6]
Generated code:
/* 001 */ public Object generate(Object[] references) {
/* 002 */ return new GeneratedIterator(references);
/* 003 */ }
/* 004 */
/* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator {
/* 006 */ private Object[] references;
/* 007 */ private boolean sagg_initAgg;
/* 008 */ private boolean sagg_bufIsNull;
/* 009 */ private UTF8String sagg_bufValue;
/* 010 */ private org.apache.spark.sql.execution.metric.SQLMetric sagg_numOutputRows;
/* 011 */ private org.apache.spark.sql.execution.metric.SQLMetric sagg_aggTime;
/* 012 */ private scala.collection.Iterator inputadapter_input;
/* 013 */ private UnsafeRow sagg_result;
/* 014 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder sagg_holder;
/* 015 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter sagg_rowWriter;
/* 016 */
/* 017 */ public GeneratedIterator(Object[] references) {
/* 018 */ this.references = references;
/* 019 */ }
/* 020 */
/* 021 */ public void init(int index, scala.collection.Iterator inputs[]) {
/* 022 */ partitionIndex = index;
/* 023 */ sagg_initAgg = false;
/* 024 */
/* 025 */ this.sagg_numOutputRows = (org.apache.spark.sql.execution.metric.SQLMetric) references[0];
/* 026 */ this.sagg_aggTime = (org.apache.spark.sql.execution.metric.SQLMetric) references[1];
/* 027 */ inputadapter_input = inputs[0];
/* 028 */ sagg_result = new UnsafeRow(1);
/* 029 */ this.sagg_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(sagg_result, 32);
/* 030 */ this.sagg_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(sagg_holder, 1);
/* 031 */ }
/* 032 */
/* 033 */ private void sagg_doAggregateWithoutKey() throws java.io.IOException {
/* 034 */ // initialize aggregation buffer
/* 035 */ final UTF8String sagg_value = null;
/* 036 */ sagg_bufIsNull = true;
/* 037 */ sagg_bufValue = sagg_value;
/* 038 */
/* 039 */ while (inputadapter_input.hasNext()) {
/* 040 */ InternalRow inputadapter_row = (InternalRow) inputadapter_input.next();
/* 041 */ boolean inputadapter_isNull = inputadapter_row.isNullAt(0);
/* 042 */ UTF8String inputadapter_value = inputadapter_isNull ? null : (inputadapter_row.getUTF8String(0));
/* 043 */
/* 044 */ // common sub-expressions
/* 045 */
/* 046 */ // evaluate aggregate function
/* 047 */ boolean sagg_isNull1 = sagg_bufIsNull;
/* 048 */ UTF8String sagg_value1 = sagg_bufValue;
/* 049 */
/* 050 */ if (!inputadapter_isNull && (sagg_isNull1 ||
/* 051 */ (inputadapter_value.compare(sagg_value1)) > 0)) {
/* 052 */ sagg_isNull1 = false;
/* 053 */ sagg_value1 = inputadapter_value;
/* 054 */ }
/* 055 */ // update aggregation buffer
/* 056 */ sagg_bufIsNull = sagg_isNull1;
/* 057 */ if (sagg_bufValue != sagg_value1)
/* 058 */ sagg_bufValue = sagg_value1 == null ? null : sagg_value1.clone();
/* 059 */ if (shouldStop()) return;
/* 060 */ }
/* 061 */
/* 062 */ }
/* 063 */
/* 064 */ protected void processNext() throws java.io.IOException {
/* 065 */ while (!sagg_initAgg) {
/* 066 */ sagg_initAgg = true;
/* 067 */ long sagg_beforeAgg = System.nanoTime();
/* 068 */ sagg_doAggregateWithoutKey();
/* 069 */ sagg_aggTime.add((System.nanoTime() - sagg_beforeAgg) / 1000000);
/* 070 */
/* 071 */ // output the result
/* 072 */
/* 073 */ sagg_numOutputRows.add(1);
/* 074 */ sagg_holder.reset();
/* 075 */
/* 076 */ sagg_rowWriter.zeroOutNullBytes();
/* 077 */
/* 078 */ if (sagg_bufIsNull) {
/* 079 */ sagg_rowWriter.setNullAt(0);
/* 080 */ } else {
/* 081 */ sagg_rowWriter.write(0, sagg_bufValue);
/* 082 */ }
/* 083 */ sagg_result.setTotalSize(sagg_holder.totalSize());
/* 084 */ append(sagg_result);
/* 085 */ }
/* 086 */ }
/* 087 */ }
== Subtree 2 / 2 ==
*SortAggregate(key=[], functions=[max(v#6)], output=[max(v)#14])
+- Exchange SinglePartition
+- *SortAggregate(key=[], functions=[partial_max(v#6)], output=[max#18])
+- LocalTableScan [v#6]
Generated code:
/* 001 */ public Object generate(Object[] references) {
/* 002 */ return new GeneratedIterator(references);
/* 003 */ }
/* 004 */
/* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator {
/* 006 */ private Object[] references;
/* 007 */ private boolean sagg_initAgg;
/* 008 */ private boolean sagg_bufIsNull;
/* 009 */ private UTF8String sagg_bufValue;
/* 010 */ private org.apache.spark.sql.execution.metric.SQLMetric sagg_numOutputRows;
/* 011 */ private org.apache.spark.sql.execution.metric.SQLMetric sagg_aggTime;
/* 012 */ private scala.collection.Iterator inputadapter_input;
/* 013 */ private UnsafeRow sagg_result;
/* 014 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder sagg_holder;
/* 015 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter sagg_rowWriter;
/* 016 */
/* 017 */ public GeneratedIterator(Object[] references) {
/* 018 */ this.references = references;
/* 019 */ }
/* 020 */
/* 021 */ public void init(int index, scala.collection.Iterator inputs[]) {
/* 022 */ partitionIndex = index;
/* 023 */ sagg_initAgg = false;
/* 024 */
/* 025 */ this.sagg_numOutputRows = (org.apache.spark.sql.execution.metric.SQLMetric) references[0];
/* 026 */ this.sagg_aggTime = (org.apache.spark.sql.execution.metric.SQLMetric) references[1];
/* 027 */ inputadapter_input = inputs[0];
/* 028 */ sagg_result = new UnsafeRow(1);
/* 029 */ this.sagg_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(sagg_result, 32);
/* 030 */ this.sagg_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(sagg_holder, 1);
/* 031 */ }
/* 032 */
/* 033 */ private void sagg_doAggregateWithoutKey() throws java.io.IOException {
/* 034 */ // initialize aggregation buffer
/* 035 */ final UTF8String sagg_value = null;
/* 036 */ sagg_bufIsNull = true;
/* 037 */ sagg_bufValue = sagg_value;
/* 038 */
/* 039 */ while (inputadapter_input.hasNext()) {
/* 040 */ InternalRow inputadapter_row = (InternalRow) inputadapter_input.next();
/* 041 */ boolean inputadapter_isNull = inputadapter_row.isNullAt(0);
/* 042 */ UTF8String inputadapter_value = inputadapter_isNull ? null : (inputadapter_row.getUTF8String(0));
/* 043 */
/* 044 */ // common sub-expressions
/* 045 */
/* 046 */ // evaluate aggregate function
/* 047 */ boolean sagg_isNull3 = sagg_bufIsNull;
/* 048 */ UTF8String sagg_value3 = sagg_bufValue;
/* 049 */
/* 050 */ if (!inputadapter_isNull && (sagg_isNull3 ||
/* 051 */ (inputadapter_value.compare(sagg_value3)) > 0)) {
/* 052 */ sagg_isNull3 = false;
/* 053 */ sagg_value3 = inputadapter_value;
/* 054 */ }
/* 055 */ // update aggregation buffer
/* 056 */ sagg_bufIsNull = sagg_isNull3;
/* 057 */ if (sagg_bufValue != sagg_value3)
/* 058 */ sagg_bufValue = sagg_value3 == null ? null : sagg_value3.clone();
/* 059 */ if (shouldStop()) return;
/* 060 */ }
/* 061 */
/* 062 */ }
/* 063 */
/* 064 */ protected void processNext() throws java.io.IOException {
/* 065 */ while (!sagg_initAgg) {
/* 066 */ sagg_initAgg = true;
/* 067 */ long sagg_beforeAgg = System.nanoTime();
/* 068 */ sagg_doAggregateWithoutKey();
/* 069 */ sagg_aggTime.add((System.nanoTime() - sagg_beforeAgg) / 1000000);
/* 070 */
/* 071 */ // output the result
/* 072 */
/* 073 */ sagg_numOutputRows.add(1);
/* 074 */ sagg_holder.reset();
/* 075 */
/* 076 */ sagg_rowWriter.zeroOutNullBytes();
/* 077 */
/* 078 */ if (sagg_bufIsNull) {
/* 079 */ sagg_rowWriter.setNullAt(0);
/* 080 */ } else {
/* 081 */ sagg_rowWriter.write(0, sagg_bufValue);
/* 082 */ }
/* 083 */ sagg_result.setTotalSize(sagg_holder.totalSize());
/* 084 */ append(sagg_result);
/* 085 */ }
/* 086 */ }
/* 087 */ }

yucai · 2016-08-17T13:18:58Z

Generated code example, not for code view yet.

scala> Seq(("a", "10"), ("b", "1"), ("b", "2"), ("c", "5"), ("c", "3")).
| toDF("k", "v").groupBy("k").agg(max("v")).debugCodegen()
Found 2 WholeStageCodegen subtrees.
== Subtree 1 / 2 ==
*SortAggregate(key=[k#24], functions=[partial_max(v#25)], output=[k#24,max#38])
+- *Sort [k#24 ASC], false, 0
+- LocalTableScan [k#24, v#25]
Generated code:
/* 001 */ public Object generate(Object[] references) {
/* 002 */ return new GeneratedIterator(references);
/* 003 */ }
/* 004 */
/* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator {
/* 006 */ private Object[] references;
/* 007 */ private boolean sagg_bufIsNull;
/* 008 */ private UTF8String sagg_bufValue;
/* 009 */ private UnsafeRow sagg_currentGroupingKey;
/* 010 */ private boolean sagg_lastAgg;
/* 011 */ private org.apache.spark.sql.execution.metric.SQLMetric sagg_numOutputRows;
/* 012 */ private boolean sort_needToSort;
/* 013 */ private org.apache.spark.sql.execution.SortExec sort_plan;
/* 014 */ private org.apache.spark.sql.execution.UnsafeExternalRowSorter sort_sorter;
/* 015 */ private org.apache.spark.executor.TaskMetrics sort_metrics;
/* 016 */ private scala.collection.Iterator<UnsafeRow> sort_sortedIter;
/* 017 */ private scala.collection.Iterator inputadapter_input;
/* 018 */ private org.apache.spark.sql.execution.metric.SQLMetric sort_peakMemory;
/* 019 */ private org.apache.spark.sql.execution.metric.SQLMetric sort_spillSize;
/* 020 */ private org.apache.spark.sql.execution.metric.SQLMetric sort_sortTime;
/* 021 */ private UnsafeRow sagg_result;
/* 022 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder sagg_holder;
/* 023 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter sagg_rowWriter;
/* 024 */ private UnsafeRow sagg_result1;
/* 025 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder sagg_holder1;
/* 026 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter sagg_rowWriter1;
/* 027 */ private UnsafeRow wholestagecodegen_result;
/* 028 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder wholestagecodegen_holder;
/* 029 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter wholestagecodegen_rowWriter;
/* 030 */
/* 031 */ public GeneratedIterator(Object[] references) {
/* 032 */ this.references = references;
/* 033 */ }
/* 034 */
/* 035 */ public void init(int index, scala.collection.Iterator inputs[]) {
/* 036 */ partitionIndex = index;
/* 037 */
/* 038 */ sagg_currentGroupingKey = null;
/* 039 */ sagg_lastAgg = true;
/* 040 */ this.sagg_numOutputRows = (org.apache.spark.sql.execution.metric.SQLMetric) references[0];
/* 041 */ sort_needToSort = true;
/* 042 */ this.sort_plan = (org.apache.spark.sql.execution.SortExec) references[1];
/* 043 */ sort_sorter = sort_plan.createSorter();
/* 044 */ sort_metrics = org.apache.spark.TaskContext.get().taskMetrics();
/* 045 */
/* 046 */ inputadapter_input = inputs[0];
/* 047 */ this.sort_peakMemory = (org.apache.spark.sql.execution.metric.SQLMetric) references[2];
/* 048 */ this.sort_spillSize = (org.apache.spark.sql.execution.metric.SQLMetric) references[3];
/* 049 */ this.sort_sortTime = (org.apache.spark.sql.execution.metric.SQLMetric) references[4];
/* 050 */ sagg_result = new UnsafeRow(1);
/* 051 */ this.sagg_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(sagg_result, 32);
/* 052 */ this.sagg_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(sagg_holder, 1);
/* 053 */ sagg_result1 = new UnsafeRow(2);
/* 054 */ this.sagg_holder1 = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(sagg_result1, 64);
/* 055 */ this.sagg_rowWriter1 = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(sagg_holder1, 2);
/* 056 */ wholestagecodegen_result = new UnsafeRow(2);
/* 057 */ this.wholestagecodegen_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(wholestagecodegen_result, 64);
/* 058 */ this.wholestagecodegen_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(wholestagecodegen_holder, 2);
/* 059 */ }
/* 060 */
/* 061 */ private void sort_addToSorter() throws java.io.IOException {
/* 062 */ while (inputadapter_input.hasNext()) {
/* 063 */ InternalRow inputadapter_row = (InternalRow) inputadapter_input.next();
/* 064 */ sort_sorter.insertRow((UnsafeRow)inputadapter_row);
/* 065 */ if (shouldStop()) return;
/* 066 */ }
/* 067 */
/* 068 */ }
/* 069 */
/* 070 */ protected void processNext() throws java.io.IOException {
/* 071 */ if (sort_needToSort) {
/* 072 */ long sort_spillSizeBefore = sort_metrics.memoryBytesSpilled();
/* 073 */ sort_addToSorter();
/* 074 */ sort_sortedIter = sort_sorter.sort();
/* 075 */ sort_sortTime.add(sort_sorter.getSortTimeNanos() / 1000000);
/* 076 */ sort_peakMemory.add(sort_sorter.getPeakMemoryUsage());
/* 077 */ sort_spillSize.add(sort_metrics.memoryBytesSpilled() - sort_spillSizeBefore);
/* 078 */ sort_metrics.incPeakExecutionMemory(sort_sorter.getPeakMemoryUsage());
/* 079 */ sort_needToSort = false;
/* 080 */ }
/* 081 */
/* 082 */ while (sort_sortedIter.hasNext()) {
/* 083 */ UnsafeRow sort_outputRow = (UnsafeRow)sort_sortedIter.next();
/* 084 */
/* 085 */ boolean sort_isNull = sort_outputRow.isNullAt(0);
/* 086 */ UTF8String sort_value = sort_isNull ? null : (sort_outputRow.getUTF8String(0));
/* 087 */ boolean sort_isNull1 = sort_outputRow.isNullAt(1);
/* 088 */ UTF8String sort_value1 = sort_isNull1 ? null : (sort_outputRow.getUTF8String(1));
/* 089 */
/* 090 */ // generate grouping key
/* 091 */ sagg_holder.reset();
/* 092 */
/* 093 */ sagg_rowWriter.zeroOutNullBytes();
/* 094 */
/* 095 */ if (sort_isNull) {
/* 096 */ sagg_rowWriter.setNullAt(0);
/* 097 */ } else {
/* 098 */ sagg_rowWriter.write(0, sort_value);
/* 099 */ }
/* 100 */ sagg_result.setTotalSize(sagg_holder.totalSize());
/* 101 */
/* 102 */ if (sagg_currentGroupingKey == null) {
/* 103 */ sagg_currentGroupingKey = sagg_result.copy();
/* 104 */ // init aggregation buffer vars
/* 105 */ final UTF8String sagg_value = null;
/* 106 */ sagg_bufIsNull = true;
/* 107 */ sagg_bufValue = sagg_value;
/* 108 */ // do aggregation
/* 109 */ // common sub-expressions
/* 110 */
/* 111 */ // evaluate aggregate function
/* 112 */ boolean sagg_isNull2 = sagg_bufIsNull;
/* 113 */ UTF8String sagg_value2 = sagg_bufValue;
/* 114 */
/* 115 */ if (!sort_isNull1 && (sagg_isNull2 ||
/* 116 */ (sort_value1.compare(sagg_value2)) > 0)) {
/* 117 */ sagg_isNull2 = false;
/* 118 */ sagg_value2 = sort_value1;
/* 119 */ }
/* 120 */ // update aggregation buffer
/* 121 */ sagg_bufIsNull = sagg_isNull2;
/* 122 */ if (sagg_bufValue != sagg_value2)
/* 123 */ sagg_bufValue = sagg_value2 == null ? null : sagg_value2.clone();
/* 124 */ continue;
/* 125 */ } else {
/* 126 */ if (sagg_currentGroupingKey.equals(sagg_result)) {
/* 127 */ // do aggregation
/* 128 */ // common sub-expressions
/* 129 */
/* 130 */ // evaluate aggregate function
/* 131 */ boolean sagg_isNull2 = sagg_bufIsNull;
/* 132 */ UTF8String sagg_value2 = sagg_bufValue;
/* 133 */
/* 134 */ if (!sort_isNull1 && (sagg_isNull2 ||
/* 135 */ (sort_value1.compare(sagg_value2)) > 0)) {
/* 136 */ sagg_isNull2 = false;
/* 137 */ sagg_value2 = sort_value1;
/* 138 */ }
/* 139 */ // update aggregation buffer
/* 140 */ sagg_bufIsNull = sagg_isNull2;
/* 141 */ if (sagg_bufValue != sagg_value2)
/* 142 */ sagg_bufValue = sagg_value2 == null ? null : sagg_value2.clone();
/* 143 */ continue;
/* 144 */ } else {
/* 145 */ do {
/* 146 */ sagg_numOutputRows.add(1);
/* 147 */
/* 148 */ sagg_holder1.reset();
/* 149 */
/* 150 */ sagg_rowWriter1.zeroOutNullBytes();
/* 151 */
/* 152 */ boolean sagg_isNull5 = sagg_currentGroupingKey.isNullAt(0);
/* 153 */ UTF8String sagg_value5 = sagg_isNull5 ? null : (sagg_currentGroupingKey.getUTF8String(0));
/* 154 */ if (sagg_isNull5) {
/* 155 */ sagg_rowWriter1.setNullAt(0);
/* 156 */ } else {
/* 157 */ sagg_rowWriter1.write(0, sagg_value5);
/* 158 */ }
/* 159 */
/* 160 */ if (sagg_bufIsNull) {
/* 161 */ sagg_rowWriter1.setNullAt(1);
/* 162 */ } else {
/* 163 */ sagg_rowWriter1.write(1, sagg_bufValue);
/* 164 */ }
/* 165 */ sagg_result1.setTotalSize(sagg_holder1.totalSize());
/* 166 */
/* 167 */ append(sagg_result1);
/* 168 */
/* 169 */ } while (false);
/* 170 */ // new grouping key
/* 171 */ sagg_currentGroupingKey = sagg_result.copy();
/* 172 */ final UTF8String sagg_value = null;
/* 173 */ sagg_bufIsNull = true;
/* 174 */ sagg_bufValue = sagg_value;
/* 175 */ // common sub-expressions
/* 176 */
/* 177 */ // evaluate aggregate function
/* 178 */ boolean sagg_isNull2 = sagg_bufIsNull;
/* 179 */ UTF8String sagg_value2 = sagg_bufValue;
/* 180 */
/* 181 */ if (!sort_isNull1 && (sagg_isNull2 ||
/* 182 */ (sort_value1.compare(sagg_value2)) > 0)) {
/* 183 */ sagg_isNull2 = false;
/* 184 */ sagg_value2 = sort_value1;
/* 185 */ }
/* 186 */ // update aggregation buffer
/* 187 */ sagg_bufIsNull = sagg_isNull2;
/* 188 */ if (sagg_bufValue != sagg_value2)
/* 189 */ sagg_bufValue = sagg_value2 == null ? null : sagg_value2.clone();
/* 190 */ }
/* 191 */ }
/* 192 */
/* 193 */ if (shouldStop()) return;
/* 194 */ }
/* 195 */
/* 196 */ while (sagg_lastAgg && sagg_currentGroupingKey != null) {
/* 197 */ sagg_lastAgg = false;
/* 198 */ sagg_numOutputRows.add(1);
/* 199 */
/* 200 */ wholestagecodegen_holder.reset();
/* 201 */
/* 202 */ wholestagecodegen_rowWriter.zeroOutNullBytes();
/* 203 */
/* 204 */ boolean wholestagecodegen_isNull = sagg_currentGroupingKey.isNullAt(0);
/* 205 */ UTF8String wholestagecodegen_value = wholestagecodegen_isNull ? null : (sagg_currentGroupingKey.getUTF8String(0));
/* 206 */ if (wholestagecodegen_isNull) {
/* 207 */ wholestagecodegen_rowWriter.setNullAt(0);
/* 208 */ } else {
/* 209 */ wholestagecodegen_rowWriter.write(0, wholestagecodegen_value);
/* 210 */ }
/* 211 */
/* 212 */ if (sagg_bufIsNull) {
/* 213 */ wholestagecodegen_rowWriter.setNullAt(1);
/* 214 */ } else {
/* 215 */ wholestagecodegen_rowWriter.write(1, sagg_bufValue);
/* 216 */ }
/* 217 */ wholestagecodegen_result.setTotalSize(wholestagecodegen_holder.totalSize());
/* 218 */
/* 219 */ append(wholestagecodegen_result);
/* 220 */
/* 221 */ }
/* 222 */ }
/* 223 */ }
== Subtree 2 / 2 ==
*SortAggregate(key=[k#24], functions=[max(v#25)], output=[k#24,max(v)#33])
+- *Sort [k#24 ASC], false, 0
+- Exchange hashpartitioning(k#24, 200)
+- *SortAggregate(key=[k#24], functions=[partial_max(v#25)], output=[k#24,max#38])
+- *Sort [k#24 ASC], false, 0
+- LocalTableScan [k#24, v#25]
Generated code:
/* 001 */ public Object generate(Object[] references) {
/* 002 */ return new GeneratedIterator(references);
/* 003 */ }
/* 004 */
/* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator {
/* 006 */ private Object[] references;
/* 007 */ private boolean sagg_bufIsNull;
/* 008 */ private UTF8String sagg_bufValue;
/* 009 */ private UnsafeRow sagg_currentGroupingKey;
/* 010 */ private boolean sagg_lastAgg;
/* 011 */ private org.apache.spark.sql.execution.metric.SQLMetric sagg_numOutputRows;
/* 012 */ private boolean sort_needToSort;
/* 013 */ private org.apache.spark.sql.execution.SortExec sort_plan;
/* 014 */ private org.apache.spark.sql.execution.UnsafeExternalRowSorter sort_sorter;
/* 015 */ private org.apache.spark.executor.TaskMetrics sort_metrics;
/* 016 */ private scala.collection.Iterator<UnsafeRow> sort_sortedIter;
/* 017 */ private scala.collection.Iterator inputadapter_input;
/* 018 */ private org.apache.spark.sql.execution.metric.SQLMetric sort_peakMemory;
/* 019 */ private org.apache.spark.sql.execution.metric.SQLMetric sort_spillSize;
/* 020 */ private org.apache.spark.sql.execution.metric.SQLMetric sort_sortTime;
/* 021 */ private UnsafeRow sagg_result;
/* 022 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder sagg_holder;
/* 023 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter sagg_rowWriter;
/* 024 */ private UnsafeRow sagg_result1;
/* 025 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder sagg_holder1;
/* 026 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter sagg_rowWriter1;
/* 027 */ private UnsafeRow wholestagecodegen_result;
/* 028 */ private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder wholestagecodegen_holder;
/* 029 */ private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter wholestagecodegen_rowWriter;
/* 030 */
/* 031 */ public GeneratedIterator(Object[] references) {
/* 032 */ this.references = references;
/* 033 */ }
/* 034 */
/* 035 */ public void init(int index, scala.collection.Iterator inputs[]) {
/* 036 */ partitionIndex = index;
/* 037 */
/* 038 */ sagg_currentGroupingKey = null;
/* 039 */ sagg_lastAgg = true;
/* 040 */ this.sagg_numOutputRows = (org.apache.spark.sql.execution.metric.SQLMetric) references[0];
/* 041 */ sort_needToSort = true;
/* 042 */ this.sort_plan = (org.apache.spark.sql.execution.SortExec) references[1];
/* 043 */ sort_sorter = sort_plan.createSorter();
/* 044 */ sort_metrics = org.apache.spark.TaskContext.get().taskMetrics();
/* 045 */
/* 046 */ inputadapter_input = inputs[0];
/* 047 */ this.sort_peakMemory = (org.apache.spark.sql.execution.metric.SQLMetric) references[2];
/* 048 */ this.sort_spillSize = (org.apache.spark.sql.execution.metric.SQLMetric) references[3];
/* 049 */ this.sort_sortTime = (org.apache.spark.sql.execution.metric.SQLMetric) references[4];
/* 050 */ sagg_result = new UnsafeRow(1);
/* 051 */ this.sagg_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(sagg_result, 32);
/* 052 */ this.sagg_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(sagg_holder, 1);
/* 053 */ sagg_result1 = new UnsafeRow(2);
/* 054 */ this.sagg_holder1 = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(sagg_result1, 64);
/* 055 */ this.sagg_rowWriter1 = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(sagg_holder1, 2);
/* 056 */ wholestagecodegen_result = new UnsafeRow(2);
/* 057 */ this.wholestagecodegen_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(wholestagecodegen_result, 64);
/* 058 */ this.wholestagecodegen_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(wholestagecodegen_holder, 2);
/* 059 */ }
/* 060 */
/* 061 */ private void sort_addToSorter() throws java.io.IOException {
/* 062 */ while (inputadapter_input.hasNext()) {
/* 063 */ InternalRow inputadapter_row = (InternalRow) inputadapter_input.next();
/* 064 */ sort_sorter.insertRow((UnsafeRow)inputadapter_row);
/* 065 */ if (shouldStop()) return;
/* 066 */ }
/* 067 */
/* 068 */ }
/* 069 */
/* 070 */ protected void processNext() throws java.io.IOException {
/* 071 */ if (sort_needToSort) {
/* 072 */ long sort_spillSizeBefore = sort_metrics.memoryBytesSpilled();
/* 073 */ sort_addToSorter();
/* 074 */ sort_sortedIter = sort_sorter.sort();
/* 075 */ sort_sortTime.add(sort_sorter.getSortTimeNanos() / 1000000);
/* 076 */ sort_peakMemory.add(sort_sorter.getPeakMemoryUsage());
/* 077 */ sort_spillSize.add(sort_metrics.memoryBytesSpilled() - sort_spillSizeBefore);
/* 078 */ sort_metrics.incPeakExecutionMemory(sort_sorter.getPeakMemoryUsage());
/* 079 */ sort_needToSort = false;
/* 080 */ }
/* 081 */
/* 082 */ while (sort_sortedIter.hasNext()) {
/* 083 */ UnsafeRow sort_outputRow = (UnsafeRow)sort_sortedIter.next();
/* 084 */
/* 085 */ boolean sort_isNull = sort_outputRow.isNullAt(0);
/* 086 */ UTF8String sort_value = sort_isNull ? null : (sort_outputRow.getUTF8String(0));
/* 087 */ boolean sort_isNull1 = sort_outputRow.isNullAt(1);
/* 088 */ UTF8String sort_value1 = sort_isNull1 ? null : (sort_outputRow.getUTF8String(1));
/* 089 */
/* 090 */ // generate grouping key
/* 091 */ sagg_holder.reset();
/* 092 */
/* 093 */ sagg_rowWriter.zeroOutNullBytes();
/* 094 */
/* 095 */ if (sort_isNull) {
/* 096 */ sagg_rowWriter.setNullAt(0);
/* 097 */ } else {
/* 098 */ sagg_rowWriter.write(0, sort_value);
/* 099 */ }
/* 100 */ sagg_result.setTotalSize(sagg_holder.totalSize());
/* 101 */
/* 102 */ if (sagg_currentGroupingKey == null) {
/* 103 */ sagg_currentGroupingKey = sagg_result.copy();
/* 104 */ // init aggregation buffer vars
/* 105 */ final UTF8String sagg_value = null;
/* 106 */ sagg_bufIsNull = true;
/* 107 */ sagg_bufValue = sagg_value;
/* 108 */ // do aggregation
/* 109 */ // common sub-expressions
/* 110 */
/* 111 */ // evaluate aggregate function
/* 112 */ boolean sagg_isNull2 = sagg_bufIsNull;
/* 113 */ UTF8String sagg_value2 = sagg_bufValue;
/* 114 */
/* 115 */ if (!sort_isNull1 && (sagg_isNull2 ||
/* 116 */ (sort_value1.compare(sagg_value2)) > 0)) {
/* 117 */ sagg_isNull2 = false;
/* 118 */ sagg_value2 = sort_value1;
/* 119 */ }
/* 120 */ // update aggregation buffer
/* 121 */ sagg_bufIsNull = sagg_isNull2;
/* 122 */ if (sagg_bufValue != sagg_value2)
/* 123 */ sagg_bufValue = sagg_value2 == null ? null : sagg_value2.clone();
/* 124 */ continue;
/* 125 */ } else {
/* 126 */ if (sagg_currentGroupingKey.equals(sagg_result)) {
/* 127 */ // do aggregation
/* 128 */ // common sub-expressions
/* 129 */
/* 130 */ // evaluate aggregate function
/* 131 */ boolean sagg_isNull2 = sagg_bufIsNull;
/* 132 */ UTF8String sagg_value2 = sagg_bufValue;
/* 133 */
/* 134 */ if (!sort_isNull1 && (sagg_isNull2 ||
/* 135 */ (sort_value1.compare(sagg_value2)) > 0)) {
/* 136 */ sagg_isNull2 = false;
/* 137 */ sagg_value2 = sort_value1;
/* 138 */ }
/* 139 */ // update aggregation buffer
/* 140 */ sagg_bufIsNull = sagg_isNull2;
/* 141 */ if (sagg_bufValue != sagg_value2)
/* 142 */ sagg_bufValue = sagg_value2 == null ? null : sagg_value2.clone();
/* 143 */ continue;
/* 144 */ } else {
/* 145 */ do {
/* 146 */ sagg_numOutputRows.add(1);
/* 147 */
/* 148 */ boolean sagg_isNull5 = sagg_currentGroupingKey.isNullAt(0);
/* 149 */ UTF8String sagg_value5 = sagg_isNull5 ? null : (sagg_currentGroupingKey.getUTF8String(0));
/* 150 */
/* 151 */ sagg_holder1.reset();
/* 152 */
/* 153 */ sagg_rowWriter1.zeroOutNullBytes();
/* 154 */
/* 155 */ if (sagg_isNull5) {
/* 156 */ sagg_rowWriter1.setNullAt(0);
/* 157 */ } else {
/* 158 */ sagg_rowWriter1.write(0, sagg_value5);
/* 159 */ }
/* 160 */
/* 161 */ if (sagg_bufIsNull) {
/* 162 */ sagg_rowWriter1.setNullAt(1);
/* 163 */ } else {
/* 164 */ sagg_rowWriter1.write(1, sagg_bufValue);
/* 165 */ }
/* 166 */ sagg_result1.setTotalSize(sagg_holder1.totalSize());
/* 167 */ append(sagg_result1);
/* 168 */
/* 169 */ } while (false);
/* 170 */ // new grouping key
/* 171 */ sagg_currentGroupingKey = sagg_result.copy();
/* 172 */ final UTF8String sagg_value = null;
/* 173 */ sagg_bufIsNull = true;
/* 174 */ sagg_bufValue = sagg_value;
/* 175 */ // common sub-expressions
/* 176 */
/* 177 */ // evaluate aggregate function
/* 178 */ boolean sagg_isNull2 = sagg_bufIsNull;
/* 179 */ UTF8String sagg_value2 = sagg_bufValue;
/* 180 */
/* 181 */ if (!sort_isNull1 && (sagg_isNull2 ||
/* 182 */ (sort_value1.compare(sagg_value2)) > 0)) {
/* 183 */ sagg_isNull2 = false;
/* 184 */ sagg_value2 = sort_value1;
/* 185 */ }
/* 186 */ // update aggregation buffer
/* 187 */ sagg_bufIsNull = sagg_isNull2;
/* 188 */ if (sagg_bufValue != sagg_value2)
/* 189 */ sagg_bufValue = sagg_value2 == null ? null : sagg_value2.clone();
/* 190 */ }
/* 191 */ }
/* 192 */
/* 193 */ if (shouldStop()) return;
/* 194 */ }
/* 195 */
/* 196 */ while (sagg_lastAgg && sagg_currentGroupingKey != null) {
/* 197 */ sagg_lastAgg = false;
/* 198 */ sagg_numOutputRows.add(1);
/* 199 */
/* 200 */ boolean wholestagecodegen_isNull = sagg_currentGroupingKey.isNullAt(0);
/* 201 */ UTF8String wholestagecodegen_value = wholestagecodegen_isNull ? null : (sagg_currentGroupingKey.getUTF8String(0));
/* 202 */
/* 203 */ wholestagecodegen_holder.reset();
/* 204 */
/* 205 */ wholestagecodegen_rowWriter.zeroOutNullBytes();
/* 206 */
/* 207 */ if (wholestagecodegen_isNull) {
/* 208 */ wholestagecodegen_rowWriter.setNullAt(0);
/* 209 */ } else {
/* 210 */ wholestagecodegen_rowWriter.write(0, wholestagecodegen_value);
/* 211 */ }
/* 212 */
/* 213 */ if (sagg_bufIsNull) {
/* 214 */ wholestagecodegen_rowWriter.setNullAt(1);
/* 215 */ } else {
/* 216 */ wholestagecodegen_rowWriter.write(1, sagg_bufValue);
/* 217 */ }
/* 218 */ wholestagecodegen_result.setTotalSize(wholestagecodegen_holder.totalSize());
/* 219 */ append(wholestagecodegen_result);
/* 220 */
/* 221 */ }
/* 222 */ }
/* 223 */ }

yucai · 2016-08-17T13:19:40Z

@chenghao-intel Hao, kindly take a look at.

chenghao-intel · 2016-08-17T15:03:08Z

@yucai can you please rebase the code?

hvanhovell · 2016-08-17T15:31:10Z

@yucai thanks for posting the benchmarks and the code. One high level comment would be to start with a properly sorted dataset for the second benchmark. I would like to know how much time is actually spend in aggregation.

maropu · 2016-11-25T09:30:23Z

@hvanhovell What's the status of this? If nobody takes this, I'll do.

yucai · 2016-11-25T10:13:01Z

@maropu, I am doing some refactor recently, will update it soon.

maropu · 2016-11-25T11:00:06Z

@yucai okay, thanks!

AmplabJenkins · 2017-01-23T21:27:20Z

Can one of the admins verify this patch?

maropu · 2017-01-24T00:59:55Z

Any update?

HyukjinKwon · 2017-05-11T13:03:01Z

gentle ping @yucai, let me propose to close this if it is still inactive.

## What changes were proposed in this pull request? This PR proposes to close PRs ... - inactive to the review comments more than a month - WIP and inactive more than a month - with Jenkins build failure but inactive more than a month - suggested to be closed and no comment against that - obviously looking inappropriate (e.g., Branch 0.5) To make sure, I left a comment for each PR about a week ago and I could not have a response back from the author in these PRs below: Closesapache#11129Closesapache#12085Closesapache#12162Closesapache#12419Closesapache#12420Closesapache#12491Closesapache#13762Closesapache#13837Closesapache#13851Closesapache#13881Closesapache#13891Closesapache#13959Closesapache#14091Closesapache#14481Closesapache#14547Closesapache#14557Closesapache#14686Closesapache#15594Closesapache#15652Closesapache#15850Closesapache#15914Closesapache#15918Closesapache#16285Closesapache#16389Closesapache#16652Closesapache#16743Closesapache#16893Closesapache#16975Closesapache#17001Closesapache#17088Closesapache#17119Closesapache#17272Closesapache#17971 Added: Closesapache#17778Closesapache#17303Closesapache#17872 ## How was this patch tested? N/A Author: hyukjinkwon <gurwls223@gmail.com> Closesapache#18017 from HyukjinKwon/close-inactive-prs.

yucai force-pushed the sortagg branch 2 times, most recently from 9048ff0 to 72a0c8aCompare August 25, 2016 15:03

yucai force-pushed the sortagg branch 4 times, most recently from 461c737 to 958dc05Compare September 22, 2016 09:13

[SPARK-16844][SQL] Generate code for sort based aggregation
eb03b2a

yucai force-pushed the sortagg branch 2 times, most recently from 0a12860 to 2c22f81Compare September 23, 2016 06:35

Create setValue to update a variable for a given DataType
4a80377

yucai force-pushed the sortagg branch from 2c22f81 to 4a80377Compare September 26, 2016 02:46

maropu mentioned this pull request Mar 4, 2017
[SPARK-16844][SQL] Support codegen for sort-based aggreagate #17164
Closed

HyukjinKwon mentioned this pull request May 17, 2017
[INFRA] Close stale PRs #18017
Closed

asfgit closed this in 5d2750aMay 18, 2017

yucai changed the title ~~[WIP][SPARK-16844][SQL] Generate code for sort based aggregation~~[SPARK-16844][SQL] Generate code for sort based aggregationDec 23, 2017

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yucai commented Aug 3, 2016•
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