HyukjinKwon opened a new pull request #33608:
URL: https://github.com/apache/spark/pull/33608
### What changes were proposed in this pull request?
This PR proposes to fail properly so JSON parser can proceed and parse the
input with the permissive mode.
Previously, we passed `null`s as are, the root `InternalRow`s became
`null`s, and it causes the query fails even with permissive mode on.
Now, we fail explicitly if `null` is passed when the input array contains
`null`.
Note that this is consistent with non-array JSON input:
**Permissive mode:**
```scala
spark.read.json(Seq("""{"a": "str"}""", """null""").toDS).collect()
```
```
res0: Array[org.apache.spark.sql.Row] = Array([str], [null])
```
**Failfast mode**:
```scala
spark.read.option("mode", "failfast").json(Seq("""{"a": "str"}""",
"""null""").toDS).collect()
```
```
org.apache.spark.SparkException: Malformed records are detected in record
parsing. Parse Mode: FAILFAST. To process malformed records as null result, try
setting the option 'mode' as 'PERMISSIVE'.
at
org.apache.spark.sql.catalyst.util.FailureSafeParser.parse(FailureSafeParser.scala:70)
at
org.apache.spark.sql.DataFrameReader.$anonfun$json$7(DataFrameReader.scala:540)
at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
```
### Why are the changes needed?
To make the permissive mode to proceed and parse without throwing an
exception.
### Does this PR introduce _any_ user-facing change?
**Permissive mode:**
```scala
spark.read.json(Seq("""[{"a": "str"}, null]""").toDS).collect()
```
Before:
```
java.lang.NullPointerException
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
```
After:
```
res0: Array[org.apache.spark.sql.Row] = Array([null])
```
NOTE that this behaviour is consistent when JSON object is malformed:
```scala
spark.read.schema("a int").json(Seq("""[{"a": 123}, {123123}, {"a":
123}]""").toDS).collect()
```
```
res0: Array[org.apache.spark.sql.Row] = Array([null])
```
Since we're parsing _one_ JSON array, related records all fail together.
**Failfast mode:**
```scala
spark.read.option("mode", "failfast").json(Seq("""[{"a": "str"},
null]""").toDS).collect()
```
Before:
```
java.lang.NullPointerException
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
```
After:
```
org.apache.spark.SparkException: Malformed records are detected in record
parsing. Parse Mode: FAILFAST. To process malformed records as null result, try
setting the option 'mode' as 'PERMISSIVE'.
at
org.apache.spark.sql.catalyst.util.FailureSafeParser.parse(FailureSafeParser.scala:70)
at
org.apache.spark.sql.DataFrameReader.$anonfun$json$7(DataFrameReader.scala:540)
at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
```
### How was this patch tested?
Manually tested, and unit test was added.
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