[SPARK-3713][SQL] Uses JSON to serialize DataType objects

This PR uses JSON instead of `toString` to serialize `DataType`s. The latter is not only hard to parse but also flaky in many cases.

Since we already write schema information to Parquet metadata in the old style, we have to reserve the old `DataType` parser and ensure downward compatibility. The old parser is now renamed to `CaseClassStringParser` and moved into `object DataType`.

JoshRosen davies Please help review PySpark related changes, thanks!

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #2563 from liancheng/datatype-to-json and squashes the following commits:

fc92eb3 [Cheng Lian] Reverts debugging code, simplifies primitive type JSON representation
438c75f [Cheng Lian] Refactors PySpark DataType JSON SerDe per comments
6b6387b [Cheng Lian] Removes debugging code
6a3ee3a [Cheng Lian] Addresses per review comments
dc158b5 [Cheng Lian] Addresses PEP8 issues
99ab4ee [Cheng Lian] Adds compatibility est case for Parquet type conversion
a983a6c [Cheng Lian] Adds PySpark support
f608c6e [Cheng Lian] De/serializes DataType objects from/to JSON

2 files changed, 8 insertions, 7 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
index 7a55c5bf97..35561cac3e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
@@ -22,6 +22,7 @@ import scala.reflect.runtime.universe.TypeTag
 
 import org.apache.hadoop.conf.Configuration
 
+import org.apache.spark.SparkContext
 import org.apache.spark.annotation.{AlphaComponent, DeveloperApi, Experimental}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.catalyst.ScalaReflection
@@ -31,12 +32,11 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.optimizer.Optimizer
 import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
 import org.apache.spark.sql.catalyst.rules.RuleExecutor
+import org.apache.spark.sql.catalyst.types.DataType
 import org.apache.spark.sql.columnar.InMemoryRelation
-import org.apache.spark.sql.execution._
-import org.apache.spark.sql.execution.SparkStrategies
+import org.apache.spark.sql.execution.{SparkStrategies, _}
 import org.apache.spark.sql.json._
 import org.apache.spark.sql.parquet.ParquetRelation
-import org.apache.spark.{Logging, SparkContext}
 
 /**
  * :: AlphaComponent ::
@@ -409,8 +409,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
    * It is only used by PySpark.
    */
   private[sql] def parseDataType(dataTypeString: String): DataType = {
-    val parser = org.apache.spark.sql.catalyst.types.DataType
-    parser(dataTypeString)
+    DataType.fromJson(dataTypeString)
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala
index 2941b97935..e6389cf77a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala
@@ -19,6 +19,8 @@ package org.apache.spark.sql.parquet
 
 import java.io.IOException
 
+import scala.util.Try
+
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.fs.{FileSystem, Path}
 import org.apache.hadoop.mapreduce.Job
@@ -323,14 +325,14 @@ private[parquet] object ParquetTypesConverter extends Logging {
   }
 
   def convertFromString(string: String): Seq[Attribute] = {
-    DataType(string) match {
+    Try(DataType.fromJson(string)).getOrElse(DataType.fromCaseClassString(string)) match {
       case s: StructType => s.toAttributes
       case other => sys.error(s"Can convert $string to row")
     }
   }
 
   def convertToString(schema: Seq[Attribute]): String = {
-    StructType.fromAttributes(schema).toString
+    StructType.fromAttributes(schema).json
   }
 
   def writeMetaData(attributes: Seq[Attribute], origPath: Path, conf: Configuration): Unit = {