## What changes were proposed in this pull request?
The original pr is: https://github.com/apache/spark/pull/18424
Add a new optimizer rule to convert an IN predicate to an equivalent Parquet filter and add `spark.sql.parquet.pushdown.inFilterThreshold` to control limit thresholds. Different data types have different limit thresholds, this is a copy of data for reference:
Type | limit threshold
-- | --
string | 370
int | 210
long | 285
double | 270
float | 220
decimal | Won't provide better performance before [SPARK-24549](https://issues.apache.org/jira/browse/SPARK-24549)
## How was this patch tested?
unit tests and manual tests
Author: Yuming Wang <yumwang@ebay.com>
Closes#21603 from wangyum/SPARK-17091.
## What changes were proposed in this pull request?
Refer to the [`WideSchemaBenchmark`](https://github.com/apache/spark/blob/v2.3.1/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/WideSchemaBenchmark.scala) update `FilterPushdownBenchmark`:
1. Write the result to `benchmarks/FilterPushdownBenchmark-results.txt` for easy maintenance.
2. Add more benchmark case: `StringStartsWith`, `Decimal`, `InSet -> InFilters` and `tinyint`.
## How was this patch tested?
manual tests
Author: Yuming Wang <yumwang@ebay.com>
Closes#21677 from wangyum/SPARK-24692.
## What changes were proposed in this pull request?
the `catalogString` for `ArrayType` and `MapType` currently calls the `simpleString` method on its children. This is a problem when the child is a struct, the `struct.simpleString` implementation truncates the number of fields it shows (25 at max). This breaks the generation of a proper `catalogString`, and has shown to cause errors while writing to Hive.
This PR fixes this by providing proper `catalogString` implementations for `ArrayData` or `MapData`.
## How was this patch tested?
Added testing for `catalogString` to `DataTypeSuite`.
Author: Herman van Hovell <hvanhovell@databricks.com>
Closes#14938 from hvanhovell/SPARK-17335.
## What changes were proposed in this pull request?
These were not updated after performance improvements. To make updating them easier, I also moved the results from inline comments out into a file, which is auto-generated when the benchmark is re-run.
Author: Eric Liang <ekl@databricks.com>
Closes#13607 from ericl/sc-3538.
