spark-instrumented-optimizer/sql/core
Corey Woodfield 8cd9cdf17a [SPARK-21333][DOCS] Removed invalid joinTypes from javadoc of Dataset#joinWith
## What changes were proposed in this pull request?

Two invalid join types were mistakenly listed in the javadoc for joinWith, in the Dataset class. I presume these were copied from the javadoc of join, but since joinWith returns a Dataset\<Tuple2\>, left_semi and left_anti are invalid, as they only return values from one of the datasets, instead of from both

## How was this patch tested?

I ran the following code :
```
public static void main(String[] args) {
	SparkSession spark = new SparkSession(new SparkContext("local[*]", "Test"));
	Dataset<Row> one = spark.createDataFrame(Arrays.asList(new Bean(1), new Bean(2), new Bean(3), new Bean(4), new Bean(5)), Bean.class);
	Dataset<Row> two = spark.createDataFrame(Arrays.asList(new Bean(4), new Bean(5), new Bean(6), new Bean(7), new Bean(8), new Bean(9)), Bean.class);

	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "inner").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "cross").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "outer").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "full").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "full_outer").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "left").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "left_outer").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "right").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "right_outer").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "left_semi").show();} catch (Exception e) {e.printStackTrace();}
	try {two.joinWith(one, one.col("x").equalTo(two.col("x")), "left_anti").show();} catch (Exception e) {e.printStackTrace();}
}
```
which tests all the different join types, and the last two (left_semi and left_anti) threw exceptions. The same code using join instead of joinWith did fine. The Bean class was just a java bean with a single int field, x.

Author: Corey Woodfield <coreywoodfield@gmail.com>

Closes #18462 from coreywoodfield/master.
2017-07-19 15:21:38 -07:00
..
benchmarks [SPARK-17335][SQL] Fix ArrayType and MapType CatalogString. 2016-09-03 19:02:20 +02:00
src [SPARK-21333][DOCS] Removed invalid joinTypes from javadoc of Dataset#joinWith 2017-07-19 15:21:38 -07:00
pom.xml [SPARK-13534][PYSPARK] Using Apache Arrow to increase performance of DataFrame.toPandas 2017-07-10 15:21:03 -07:00