from_json cannot support line separator in the input string.

[Feng-Jiang28]

from_json when there is a new line/line separator in the input results in an exception being thrown.

Reproduce:

CPU:

scala> import org.apache.spark.sql.{SparkSession, Row}
import org.apache.spark.sql.{SparkSession, Row}

scala> import org.apache.spark.sql.functions._
import org.apache.spark.sql.functions._

scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._

scala> 

scala> val spark = SparkSession.builder.appName("Test").getOrCreate()
24/05/28 15:43:57 WARN SparkSession: Using an existing Spark session; only runtime SQL configurations will take effect.
spark: org.apache.spark.sql.SparkSession = org.apache.spark.sql.SparkSession@58f6dab9

scala> import spark.implicits._
import spark.implicits._

scala> val input = """{
     |   |  "a": 1,
     |   |  "c": "foo"
     |   |}
     |   |""".stripMargin
input: String =
"{
  "a": 1,
  "c": "foo"
}
"

scala> val jsonSchema = new StructType().add("a", LongType, nullable = false).add("b", StringType, nullable = false).add("c", StringType, nullable = false)
jsonSchema: org.apache.spark.sql.types.StructType = StructType(StructField(a,LongType,false),StructField(b,StringType,false),StructField(c,StringType,false))

scala> val jsonData = Seq(input).toDS()
jsonData: org.apache.spark.sql.Dataset[String] = [value: string]

scala> val df = jsonData.toDF("jsonString")
df: org.apache.spark.sql.DataFrame = [jsonString: string]

scala> 

scala> df.write.mode("OVERWRITE").parquet("TEMP")
                                                                                
scala> val df2 = spark.read.parquet("TEMP")
df2: org.apache.spark.sql.DataFrame = [jsonString: string]

scala> val parsedDF = df2.select(from_json(col("jsonString"), jsonSchema).as("data"))
parsedDF: org.apache.spark.sql.DataFrame = [data: struct<a: bigint, b: string ... 1 more field>]

scala>   .select("data.*")
res1: org.apache.spark.sql.DataFrame = [a: bigint, b: string ... 1 more field]

scala> parsedDF.show(false)
+--------------+                                                                
|data          |
+--------------+
|{1, null, foo}|
+--------------+


scala> parsedDF.printSchema()
root
 |-- data: struct (nullable = true)
 |    |-- a: long (nullable = true)
 |    |-- b: string (nullable = true)
 |    |-- c: string (nullable = true)


scala> spark.stop()

GPU:

:~$ $SPARK_HOME/bin/spark-shell --master local[*] --jars ${SPARK_RAPIDS_PLUGIN_JAR} 
--conf spark.plugins=com.nvidia.spark.SQLPlugin 
--conf spark.rapids.sql.enabled=true 
--conf spark.rapids.sql.explain=ALL 
--driver-java-options '-ea -Duser.timezone=UTC ' 
--conf spark.rapids.sql.expression.JsonTuple=true 
--conf spark.rapids.sql.expression.GetJsonObject=true 
--conf spark.rapids.sql.expression.JsonToStructs=true 
--conf spark.rapids.sql.expression.StructsToJson=true

scala> import org.apache.spark.sql.{SparkSession, Row}
import org.apache.spark.sql.{SparkSession, Row}

scala> import org.apache.spark.sql.functions._
import org.apache.spark.sql.functions._

scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._

scala> 

scala> val spark = SparkSession.builder.appName("Test").getOrCreate()
24/05/28 07:45:26 WARN Utils: Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
24/05/28 07:45:26 WARN RapidsPluginUtils: RAPIDS Accelerator is enabled, to disable GPU support set `spark.rapids.sql.enabled` to false.
24/05/28 07:45:26 WARN RapidsPluginUtils: spark.rapids.sql.explain is set to `ALL`. Set it to 'NONE' to suppress the diagnostics logging about the query placement on the GPU.
spark: org.apache.spark.sql.SparkSession = org.apache.spark.sql.SparkSession@64a97889

scala> import spark.implicits._
import spark.implicits._

scala> val input = """{
     |   |  "a": 1,
     |   |  "c": "foo"
     |   |}
     |   |""".stripMargin
input: String =
"{
  "a": 1,
  "c": "foo"
}
"

scala> val jsonSchema = new StructType().add("a", LongType, nullable = false).add("b", StringType, nullable = false).add("c", StringType, nullable = false)
jsonSchema: org.apache.spark.sql.types.StructType = StructType(StructField(a,LongType,false),StructField(b,StringType,false),StructField(c,StringType,false))

scala> val jsonData = Seq(input).toDS()
jsonData: org.apache.spark.sql.Dataset[String] = [value: string]

scala> val df = jsonData.toDF("jsonString")
df: org.apache.spark.sql.DataFrame = [jsonString: string]

scala> 

scala> df.write.mode("OVERWRITE").parquet("TEMP")
24/05/28 07:45:29 WARN GpuOverrides: 
*Exec <DataWritingCommandExec> will run on GPU
  *Output <InsertIntoHadoopFsRelationCommand> will run on GPU
  ! <LocalTableScanExec> cannot run on GPU because GPU does not currently support the operator class org.apache.spark.sql.execution.LocalTableScanExec
    @Expression <AttributeReference> jsonString#93 could run on GPU


scala> val df2 = spark.read.parquet("TEMP")
df2: org.apache.spark.sql.DataFrame = [jsonString: string]

scala> val parsedDF = df2.select(from_json(col("jsonString"), jsonSchema).as("data"))
parsedDF: org.apache.spark.sql.DataFrame = [data: struct<a: bigint, b: string ... 1 more field>]

scala>   .select("data.*")
res20: org.apache.spark.sql.DataFrame = [a: bigint, b: string ... 1 more field]

scala> parsedDF.show(false)
24/05/28 07:45:29 WARN GpuOverrides: 
!Exec <CollectLimitExec> cannot run on GPU because the Exec CollectLimitExec has been disabled, and is disabled by default because Collect Limit replacement can be slower on the GPU, if huge number of rows in a batch it could help by limiting the number of rows transferred from GPU to CPU. Set spark.rapids.sql.exec.CollectLimitExec to true if you wish to enable it
  @Partitioning <SinglePartition$> could run on GPU
  *Exec <ProjectExec> will run on GPU
    *Expression <Alias> cast(from_json(StructField(a,LongType,false), StructField(b,StringType,false), StructField(c,StringType,false), jsonString#96, Some(UTC)) as string) AS data#108 will run on GPU
      *Expression <Cast> cast(from_json(StructField(a,LongType,false), StructField(b,StringType,false), StructField(c,StringType,false), jsonString#96, Some(UTC)) as string) will run on GPU
        *Expression <JsonToStructs> from_json(StructField(a,LongType,false), StructField(b,StringType,false), StructField(c,StringType,false), jsonString#96, Some(UTC)) will run on GPU
    *Exec <FileSourceScanExec> will run on GPU

24/05/28 07:45:29 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 3)
java.lang.IllegalArgumentException: We cannot currently support parsing JSON that contains a line separator in it
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$checkForNewline$3(GpuJsonToStructs.scala:144)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$checkForNewline$3$adapted(GpuJsonToStructs.scala:141)
	at com.nvidia.spark.rapids.Arm$.withResource(Arm.scala:30)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$checkForNewline$2(GpuJsonToStructs.scala:141)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$checkForNewline$2$adapted(GpuJsonToStructs.scala:140)
	at com.nvidia.spark.rapids.Arm$.withResource(Arm.scala:30)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$checkForNewline$1(GpuJsonToStructs.scala:140)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$checkForNewline$1$adapted(GpuJsonToStructs.scala:139)
	at com.nvidia.spark.rapids.Arm$.withResource(Arm.scala:30)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.checkForNewline(GpuJsonToStructs.scala:139)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$cleanAndConcat$12(GpuJsonToStructs.scala:116)
	at com.nvidia.spark.rapids.Arm$.withResource(Arm.scala:30)
	at org.apache.spark.sql.rapids.GpuJsonToStructs.$anonfun$cleanAndConcat$11(GpuJsonToStructs.scala:115)
	at com.nvidia.spark.rapids.Arm$.withResource(Arm.scala:30)

[revans2]

I believe that #11549 will fix this issue