fix maptype doesn't use the frameless injection properly

Author: ukby1234

build.sbt

@@ -105,7 +105,25 @@ lazy val `sparksql-scalapb` = (projectMatrix in file("sparksql-scalapb"))
       scalapbPlugin(scalapb.value.scalapbVersion) -> (Test / sourceManaged).value
     ),
     Test / run / fork := true,
-    Test / javaOptions ++= Seq("-Xmx2G")
+    Test / fork := true,
+    Test / javaOptions ++= Seq(
+      "-Xmx2G",
+      "-XX:+IgnoreUnrecognizedVMOptions",
+      "--add-opens=java.base/java.lang=ALL-UNNAMED",
+      "--add-opens=java.base/java.lang.invoke=ALL-UNNAMED",
+      "--add-opens=java.base/java.lang.reflect=ALL-UNNAMED",
+      "--add-opens=java.base/java.io=ALL-UNNAMED",
+      "--add-opens=java.base/java.net=ALL-UNNAMED",
+      "--add-opens=java.base/java.nio=ALL-UNNAMED",
+      "--add-opens=java.base/java.util=ALL-UNNAMED",
+      "--add-opens=java.base/java.util.concurrent=ALL-UNNAMED",
+      "--add-opens=java.base/java.util.concurrent.atomic=ALL-UNNAMED",
+      "--add-opens=java.base/jdk.internal.ref=ALL-UNNAMED",
+      "--add-opens=java.base/sun.nio.ch=ALL-UNNAMED",
+      "--add-opens=java.base/sun.nio.cs=ALL-UNNAMED",
+      "--add-opens=java.base/sun.security.action=ALL-UNNAMED",
+      "--add-opens=java.base/sun.util.calendar=ALL-UNNAMED"
+    )
   )
   .customRow(
     scalaVersions = Seq(Scala212, Scala213),

sparksql-scalapb/src/main/scala/scalapb/spark/FromCatalystHelpers.scala

@@ -97,7 +97,7 @@ trait FromCatalystHelpers {
         input,
         (in: Expression) => singleFieldValueFromCatalyst(mapEntryCmp, keyDesc, in),
         (in: Expression) => singleFieldValueFromCatalyst(mapEntryCmp, valDesc, in),
-        ProtoSQL.dataTypeFor(fd).asInstanceOf[MapType],
+        protoSql.dataTypeFor(fd).asInstanceOf[MapType],
         classOf[Vector[(Any, Any)]]
       )
       val objs = MyCatalystToExternalMap(urobjs)

sparksql-scalapb/src/test/protobuf/customizations.proto

@@ -22,3 +22,7 @@ message BothTimestampTypes {
   google.protobuf.Timestamp google_ts = 1;
   google.protobuf.Timestamp google_ts_as_sql_ts = 2 [(scalapb.field).type = "java.sql.Timestamp"];
 }
+
+message TimestampTypesMap {
+  map<string, SQLTimestampFromGoogleTimestamp> map_field = 1;
+}

sparksql-scalapb/src/test/assets/address.json sparksql-scalapb/src/test/resources/address.json

@@ -310,7 +310,7 @@ class PersonSpec extends AnyFlatSpec with Matchers with BeforeAndAfterAll {
   }
 
   "UDFs that returns protos" should "work when reading local files" in {
-    val df = spark.read.json("./sparksql-scalapb/src/test/assets/address.json")
+    val df = spark.read.json(getClass.getResource("/address.json").toURI.toString)
 
     val returnAddress = ProtoSQL.udf { s: String => Address() }
 
@@ -349,7 +349,7 @@ class PersonSpec extends AnyFlatSpec with Matchers with BeforeAndAfterAll {
   "parsing null repeated from json" should "work" in {
     spark.read
       .schema(ProtoSQL.schemaFor[Person].asInstanceOf[types.StructType])
-      .json("./sparksql-scalapb/src/test/assets/person_null_repeated.json")
+      .json(getClass.getResource("/person_null_repeated.json").toURI.toString)
       .as[Person]
       .collect() must contain theSameElementsAs Seq(
       Person().withTags(Seq("foo", "bar")),

sparksql-scalapb/src/test/assets/person_null_repeated.json sparksql-scalapb/src/test/resources/person_null_repeated.json

@@ -8,7 +8,8 @@ import org.scalatest.matchers.must.Matchers
 import scalapb.spark.test3.customizations.{
   BothTimestampTypes,
   SQLTimestampFromGoogleTimestamp,
-  StructFromGoogleTimestamp
+  StructFromGoogleTimestamp,
+  TimestampTypesMap
 }
 
 import java.sql.{Timestamp => SQLTimestamp}
@@ -158,6 +159,21 @@ class TimestampSpec extends AnyFlatSpec with Matchers with BeforeAndAfterAll {
     )
   }
 
+  "spark.createDataset from proto messages with spark timestamp in map" should "be able to convert items with correct timestamp values" in {
+    import ProtoSQL.withSparkTimestamps.implicits._
+
+    val value = TimestampTypesMap(mapField =
+      Map(
+        "a" -> SQLTimestampFromGoogleTimestamp(googleTsAsSqlTs = Some(sqlTimestampMicrosPrecision))
+      )
+    )
+    val ds: Dataset[TimestampTypesMap] = spark.createDataset(Seq(value))
+
+    ds.collect() must contain theSameElementsAs Seq(
+      value
+    )
+  }
+
   "df with case class timestamp as well as both types of google timestamp" should "not have StructType for timestamps" in {
     import ProtoSQL.withSparkTimestamps.implicits._