From 369a148e591bb16ec7da54867610b207602cd698 Mon Sep 17 00:00:00 2001
From: hyukjinkwon <gurwls223@gmail.com>
Date: Sun, 5 Mar 2017 14:35:06 -0800
Subject: [SPARK-19595][SQL] Support json array in from_json

## What changes were proposed in this pull request?

This PR proposes to both,

**Do not allow json arrays with multiple elements and return null in `from_json` with `StructType` as the schema.**

Currently, it only reads the single row when the input is a json array. So, the codes below:

```scala
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types._
val schema = StructType(StructField("a", IntegerType) :: Nil)
Seq(("""[{"a": 1}, {"a": 2}]""")).toDF("struct").select(from_json(col("struct"), schema)).show()
```
prints

```
+--------------------+
|jsontostruct(struct)|
+--------------------+
|                 [1]|
+--------------------+
```

This PR simply suggests to print this as `null` if the schema is `StructType` and input is json array.with multiple elements

```
+--------------------+
|jsontostruct(struct)|
+--------------------+
|                null|
+--------------------+
```

**Support json arrays in `from_json` with `ArrayType` as the schema.**

```scala
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types._
val schema = ArrayType(StructType(StructField("a", IntegerType) :: Nil))
Seq(("""[{"a": 1}, {"a": 2}]""")).toDF("array").select(from_json(col("array"), schema)).show()
```

prints

```
+-------------------+
|jsontostruct(array)|
+-------------------+
|         [[1], [2]]|
+-------------------+
```

## How was this patch tested?

Unit test in `JsonExpressionsSuite`, `JsonFunctionsSuite`, Python doctests and manual test.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16929 from HyukjinKwon/disallow-array.
---
 .../org/apache/spark/sql/JsonFunctionsSuite.scala  | 25 +++++++++++++++++++++-
 1 file changed, 24 insertions(+), 1 deletion(-)

(limited to 'sql/core/src/test')

diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
index 9c39b3c7f0..953d161ec2 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
@@ -19,7 +19,7 @@ package org.apache.spark.sql
 
 import org.apache.spark.sql.functions.{from_json, struct, to_json}
 import org.apache.spark.sql.test.SharedSQLContext
-import org.apache.spark.sql.types.{CalendarIntervalType, IntegerType, StructType, TimestampType}
+import org.apache.spark.sql.types._
 
 class JsonFunctionsSuite extends QueryTest with SharedSQLContext {
   import testImplicits._
@@ -133,6 +133,29 @@ class JsonFunctionsSuite extends QueryTest with SharedSQLContext {
       Row(null) :: Nil)
   }
 
+  test("from_json invalid schema") {
+    val df = Seq("""{"a" 1}""").toDS()
+    val schema = ArrayType(StringType)
+    val message = intercept[AnalysisException] {
+      df.select(from_json($"value", schema))
+    }.getMessage
+
+    assert(message.contains(
+      "Input schema array<string> must be a struct or an array of structs."))
+  }
+
+  test("from_json array support") {
+    val df = Seq("""[{"a": 1, "b": "a"}, {"a": 2}, { }]""").toDS()
+    val schema = ArrayType(
+      StructType(
+        StructField("a", IntegerType) ::
+        StructField("b", StringType) :: Nil))
+
+    checkAnswer(
+      df.select(from_json($"value", schema)),
+      Row(Seq(Row(1, "a"), Row(2, null), Row(null, null))))
+  }
+
   test("to_json") {
     val df = Seq(Tuple1(Tuple1(1))).toDF("a")
 
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