[SPARK-21264][PYTHON] Call cross join path in join without 'on' and with 'how'

## What changes were proposed in this pull request?

Currently, it throws a NPE when missing columns but join type is speicified in join at PySpark as below:

```python
spark.conf.set("spark.sql.crossJoin.enabled", "false")
spark.range(1).join(spark.range(1), how="inner").show()
```

```
Traceback (most recent call last):
...
py4j.protocol.Py4JJavaError: An error occurred while calling o66.join.
: java.lang.NullPointerException
	at org.apache.spark.sql.Dataset.join(Dataset.scala:931)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
...
```

```python
spark.conf.set("spark.sql.crossJoin.enabled", "true")
spark.range(1).join(spark.range(1), how="inner").show()
```

```
...
py4j.protocol.Py4JJavaError: An error occurred while calling o84.join.
: java.lang.NullPointerException
	at org.apache.spark.sql.Dataset.join(Dataset.scala:931)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
...
```

This PR suggests to follow Scala's one as below:

```scala
scala> spark.conf.set("spark.sql.crossJoin.enabled", "false")

scala> spark.range(1).join(spark.range(1), Seq.empty[String], "inner").show()
```

```
org.apache.spark.sql.AnalysisException: Detected cartesian product for INNER join between logical plans
Range (0, 1, step=1, splits=Some(8))
and
Range (0, 1, step=1, splits=Some(8))
Join condition is missing or trivial.
Use the CROSS JOIN syntax to allow cartesian products between these relations.;
...
```

```scala
scala> spark.conf.set("spark.sql.crossJoin.enabled", "true")

scala> spark.range(1).join(spark.range(1), Seq.empty[String], "inner").show()
```
```
+---+---+
| id| id|
+---+---+
|  0|  0|
+---+---+
```

**After**

```python
spark.conf.set("spark.sql.crossJoin.enabled", "false")
spark.range(1).join(spark.range(1), how="inner").show()
```

```
Traceback (most recent call last):
...
pyspark.sql.utils.AnalysisException: u'Detected cartesian product for INNER join between logical plans\nRange (0, 1, step=1, splits=Some(8))\nand\nRange (0, 1, step=1, splits=Some(8))\nJoin condition is missing or trivial.\nUse the CROSS JOIN syntax to allow cartesian products between these relations.;'
```

```python
spark.conf.set("spark.sql.crossJoin.enabled", "true")
spark.range(1).join(spark.range(1), how="inner").show()
```
```
+---+---+
| id| id|
+---+---+
|  0|  0|
+---+---+
```

## How was this patch tested?

Added tests in `python/pyspark/sql/tests.py`.

Author: hyukjinkwon <[email protected]>

Closes #18484 from HyukjinKwon/SPARK-21264.

Author: HyukjinKwon

python/pyspark/sql/dataframe.py

@@ -833,6 +833,8 @@ def join(self, other, on=None, how=None):
         else:
             if how is None:
                 how = "inner"
+            if on is None:
+                on = self._jseq([])
             assert isinstance(how, basestring), "how should be basestring"
             jdf = self._jdf.join(other._jdf, on, how)
         return DataFrame(jdf, self.sql_ctx)

python/pyspark/sql/tests.py

@@ -2021,6 +2021,22 @@ def test_toDF_with_schema_string(self):
         self.assertEqual(df.schema.simpleString(), "struct<value:int>")
         self.assertEqual(df.collect(), [Row(key=i) for i in range(100)])
 
+    def test_join_without_on(self):
+        df1 = self.spark.range(1).toDF("a")
+        df2 = self.spark.range(1).toDF("b")
+
+        try:
+            self.spark.conf.set("spark.sql.crossJoin.enabled", "false")
+            self.assertRaises(AnalysisException, lambda: df1.join(df2, how="inner").collect())
+
+            self.spark.conf.set("spark.sql.crossJoin.enabled", "true")
+            actual = df1.join(df2, how="inner").collect()
+            expected = [Row(a=0, b=0)]
+            self.assertEqual(actual, expected)
+        finally:
+            # We should unset this. Otherwise, other tests are affected.
+            self.spark.conf.unset("spark.sql.crossJoin.enabled")
+
     # Regression test for invalid join methods when on is None, Spark-14761
     def test_invalid_join_method(self):
         df1 = self.spark.createDataFrame([("Alice", 5), ("Bob", 8)], ["name", "age"])