sunchao opened a new pull request #32104:
URL: https://github.com/apache/spark/pull/32104
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### What changes were proposed in this pull request?
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Implements `readShorts` in `VectorizedPlainValuesReader`, which decodes
`total` shorts in the input buffer at one time, similar to other types.
### Why are the changes needed?
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Currently `VectorizedRleValuesReader` reads short integer in the following
way:
```java
for (int i = 0; i < n; i++) {
c.putShort(rowId + i, (short)data.readInteger());
}
```
For PLAIN encoding `data.readInteger` is done via:
```java
public final int readInteger() {
return getBuffer(4).getInt();
}
```
which means it needs to repeatedly call `slice` buffer for the batch size
number of times. This is more expensive than calling it once in a big chunk and
then reading the ints out.
Micro benchmark via `DataSourceReadBenchmark` showed ~35% perf improvement.
Before:
```
[info] OpenJDK 64-Bit Server VM 11.0.8+10-LTS on Mac OS X 10.16
[info] Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz
[info] SQL Single SMALLINT Column Scan: Best Time(ms) Avg
Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
[info]
------------------------------------------------------------------------------------------------------------------------
[info] SQL CSV 10249
10271 32 1.5 651.6 1.0X
[info] SQL Json 5963
5982 28 2.6 379.1 1.7X
[info] SQL Parquet Vectorized 141
151 15 111.9 8.9 72.9X
[info] SQL Parquet MR 1454
1491 52 10.8 92.4 7.0X
[info] SQL ORC Vectorized 160
164 3 98.3 10.2 64.1X
[info] SQL ORC MR 1133
1164 44 13.9 72.0 9.0X
```
After:
```
[info] OpenJDK 64-Bit Server VM 11.0.8+10-LTS on Mac OS X 10.16
[info] Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz
[info] SQL Single SMALLINT Column Scan: Best Time(ms) Avg
Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
[info]
------------------------------------------------------------------------------------------------------------------------
[info] SQL CSV 10489
10535 65 1.5 666.8 1.0X
[info] SQL Json 5864
5888 34 2.7 372.8 1.8X
[info] SQL Parquet Vectorized 104
111 8 151.0 6.6 100.7X
[info] SQL Parquet MR 1458
1472 20 10.8 92.7 7.2X
[info] SQL ORC Vectorized 157
166 7 100.0 10.0 66.7X
[info] SQL ORC MR 1121
1147 37 14.0 71.2 9.4X
```
### Does this PR introduce _any_ user-facing change?
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No
### How was this patch tested?
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Existing tests
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