[VARIANT] Add variant integration tests (#3220)

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#### Which Delta project/connector is this regarding?
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- [x] Spark
- [ ] Standalone
- [ ] Flink
- [ ] Kernel
- [ ] Other (fill in here)

## Description

adds an integration test for variant to create and insert variant values
using sql and scala API
## How was this patch tested?

test only change.

Haven't been able to run this in the integration testing framework yet.
However, manually tested this in spark shell using instructions
[here](https://docs.google.com/document/d/1gpxcKZitSGf0K217kJa8eOaq5y-BDnDKpcuQ3JCjNCE/edit#heading=h.ybzt6s7hn9ff)

## Does this PR introduce _any_ user-facing changes?

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no

---------

Co-authored-by: Allison Portis <[email protected]>

Author: richardc-db

examples/scala/src/main/scala/example/Variant.scala

@@ -0,0 +1,106 @@
+/*
+ * Copyright (2024) The Delta Lake Project Authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package example
+
+import io.delta.tables.DeltaTable
+
+import org.apache.spark.sql.SparkSession
+
+object Variant {
+
+  def main(args: Array[String]): Unit = {
+    val tableName = "tbl"
+
+    val spark = SparkSession
+      .builder()
+      .appName("Variant-Delta")
+      .master("local[*]")
+      .config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension")
+      .config("spark.sql.catalog.spark_catalog", "org.apache.spark.sql.delta.catalog.DeltaCatalog")
+      .getOrCreate()
+
+    // Create and insert variant values.
+    try {
+      spark.sql(s"DROP TABLE IF EXISTS $tableName")
+      spark.sql(s"CREATE TABLE $tableName(v VARIANT) USING DELTA")
+      spark.sql(s"INSERT INTO $tableName VALUES (parse_json('1'))")
+      spark.sql(s"""INSERT INTO $tableName SELECT parse_json(format_string('{\"k\": %s}', id))
+                FROM range(0, 10)""")
+      val ids = spark.sql("SELECT variant_get(v, '$.k', 'INT') out " +
+                          s"""FROM $tableName WHERE contains(schema_of_variant(v), 'k')
+                          ORDER BY out""")
+                          .collect().map { r => r.getInt(0) }.toSeq
+      val expected = (0 until 10).toSeq
+      assert(expected == ids)
+
+      spark.sql("DELETE FROM tbl WHERE variant_get(v, '$.k', 'INT') = 0")
+      val idsWithDelete = spark.sql("SELECT variant_get(v, '$.k', 'INT') out " +
+                                    s"""FROM $tableName WHERE contains(schema_of_variant(v), 'k')
+                                    ORDER BY out""")
+                                    .collect().map { r => r.getInt(0) }.toSeq
+      val expectedWithDelete = (1 until 10).toSeq
+      assert(idsWithDelete == expectedWithDelete)
+    } finally {
+      spark.sql(s"DROP TABLE IF EXISTS $tableName")
+    }
+    
+    // Convert Parquet table with variant values to Delta.
+    try {
+      spark.sql(s"DROP TABLE IF EXISTS $tableName")
+      spark.sql("""CREATE TABLE tbl USING PARQUET AS (
+        SELECT parse_json(format_string('%s', id)) v FROM range(0, 10))""")
+      spark.sql(s"CONVERT TO DELTA $tableName")
+      val convertToDeltaIds = spark.sql(s"SELECT v::int v FROM $tableName ORDER BY v")
+        .collect()
+        .map { r => r.getInt(0) }
+        .toSeq
+      val convertToDeltaExpected = (0 until 10).toSeq
+      assert(convertToDeltaIds == convertToDeltaExpected)
+    } finally {
+      spark.sql(s"DROP TABLE IF EXISTS $tableName")
+    }
+
+    // DeltaTable create with variant Scala API.
+    try {
+      spark.sql(s"DROP TABLE IF EXISTS $tableName")
+      val table = io.delta.tables.DeltaTable.create()
+        .tableName(tableName)
+        .addColumn("v", "VARIANT")
+        .execute()
+
+      table
+        .as("tgt")
+        .merge(
+          spark.sql("select parse_json(format_string('%s', id)) v from range(0, 10)").as("source"),
+          "source.v::int == tgt.v::int"
+        )
+        .whenMatched()
+        .updateAll()
+        .whenNotMatched()
+        .insertAll()
+        .execute()
+      val insertedVals = spark.sql(s"SELECT v::int v FROM $tableName ORDER BY v")
+        .collect()
+        .map { r => r.getInt(0) }
+        .toSeq
+      val expected = (0 until 10).toSeq
+      assert(insertedVals == expected)
+    } finally {
+      spark.sql(s"DROP TABLE IF EXISTS $tableName")
+      spark.stop()
+    }
+  }
+}