[GitHub] [spark] cloud-fan commented on a change in pull request #29939: [SPARK-33062][SQL] Make DataFrameReader.jdbc work for DataSource V2

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cloud-fan commented on a change in pull request #29939:
URL: https://github.com/apache/spark/pull/29939#discussion_r501441101



##########
File path: sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCV2Suite.scala
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@@ -221,4 +221,21 @@ class JDBCV2Suite extends QueryTest with SharedSparkSession {
       checkAnswer(sql("SELECT name, id FROM h2.test.abc"), Row("bob", 4))
     }
   }
+
+  test("DataFrameReader: jdbc") {
+    withTable("h2.test.abc") {
+      sql("CREATE TABLE h2.test.abc USING _ AS SELECT * FROM h2.test.people")
+      val properties = new Properties()
+      val df1 = spark.read.jdbc(url, "h2.test.abc", properties)

Review comment:
       I'm a bit confused about this. There are 3 ways to use JDBC data source:
   1. use `DataFrameReader/Writer` API to access JDBC tables/queries directly.
   1. register as a table, and access the table.
   1. register as a catalog, and access tables inside the catalog.
   
   `spark.read.jdbc(url, "h2.test.abc", properties)` seems like a mix of 1 and 3. What's the use case you are targeting?
   




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