[SPARK-15171][SQL] Deprecate registerTempTable and add dataset.createTempView

## What changes were proposed in this pull request?

Deprecates registerTempTable and add dataset.createTempView, dataset.createOrReplaceTempView.

## How was this patch tested?

Unit tests.

Author: Sean Zhong <seanzhong@databricks.com>

Closes #12945 from clockfly/spark-15171.

6 files changed, 10 insertions, 10 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java b/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java
index d956750dc7..cf0167f13a 100644
--- a/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java
+++ b/examples/src/main/java/org/apache/spark/examples/sql/JavaSparkSQL.java
@@ -75,7 +75,7 @@ public class JavaSparkSQL {
 
     // Apply a schema to an RDD of Java Beans and register it as a table.
     Dataset<Row> schemaPeople = spark.createDataFrame(people, Person.class);
-    schemaPeople.registerTempTable("people");
+    schemaPeople.createOrReplaceTempView("people");
 
     // SQL can be run over RDDs that have been registered as tables.
     Dataset<Row> teenagers = spark.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19");
@@ -102,7 +102,7 @@ public class JavaSparkSQL {
     Dataset<Row> parquetFile = spark.read().parquet("people.parquet");
 
     //Parquet files can also be registered as tables and then used in SQL statements.
-    parquetFile.registerTempTable("parquetFile");
+    parquetFile.createOrReplaceTempView("parquetFile");
     Dataset<Row> teenagers2 =
       spark.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19");
     teenagerNames = teenagers2.toJavaRDD().map(new Function<Row, String>() {
@@ -131,7 +131,7 @@ public class JavaSparkSQL {
     //  |-- name: StringType
 
     // Register this DataFrame as a table.
-    peopleFromJsonFile.registerTempTable("people");
+    peopleFromJsonFile.createOrReplaceTempView("people");
 
     // SQL statements can be run by using the sql methods provided by `spark`
     Dataset<Row> teenagers3 = spark.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19");
@@ -163,7 +163,7 @@ public class JavaSparkSQL {
     //  |    |-- state: StringType
     //  |-- name: StringType
 
-    peopleFromJsonRDD.registerTempTable("people2");
+    peopleFromJsonRDD.createOrReplaceTempView("people2");
 
     Dataset<Row> peopleWithCity = spark.sql("SELECT name, address.city FROM people2");
     List<String> nameAndCity = peopleWithCity.toJavaRDD().map(new Function<Row, String>() {
diff --git a/examples/src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java
index 57953ef74f..5130522770 100644
--- a/examples/src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java
@@ -95,7 +95,7 @@ public final class JavaSqlNetworkWordCount {
         Dataset<Row> wordsDataFrame = spark.createDataFrame(rowRDD, JavaRecord.class);
 
         // Register as table
-        wordsDataFrame.registerTempTable("words");
+        wordsDataFrame.createOrReplaceTempView("words");
 
         // Do word count on table using SQL and print it
         Dataset<Row> wordCountsDataFrame =
diff --git a/examples/src/main/python/sql.py b/examples/src/main/python/sql.py
index d2e895d931..234024063f 100644
--- a/examples/src/main/python/sql.py
+++ b/examples/src/main/python/sql.py
@@ -67,7 +67,7 @@ if __name__ == "__main__":
     #  |-- name: string (nullable = true)
 
     # Register this DataFrame as a temporary table.
-    people.registerTempTable("people")
+    people.createOrReplaceTempView("people")
 
     # SQL statements can be run by using the sql methods provided by `spark`
     teenagers = spark.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19")
diff --git a/examples/src/main/python/streaming/sql_network_wordcount.py b/examples/src/main/python/streaming/sql_network_wordcount.py
index f8801d4ea6..25e821534e 100644
--- a/examples/src/main/python/streaming/sql_network_wordcount.py
+++ b/examples/src/main/python/streaming/sql_network_wordcount.py
@@ -71,7 +71,7 @@ if __name__ == "__main__":
             wordsDataFrame = spark.createDataFrame(rowRdd)
 
             # Register as table
-            wordsDataFrame.registerTempTable("words")
+            wordsDataFrame.createOrReplaceTempView("words")
 
             # Do word count on table using SQL and print it
             wordCountsDataFrame = \
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
index 94c378ae4b..d1bda0ff84 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
@@ -37,7 +37,7 @@ object RDDRelation {
     val df = spark.createDataFrame((1 to 100).map(i => Record(i, s"val_$i")))
     // Any RDD containing case classes can be registered as a table.  The schema of the table is
     // automatically inferred using scala reflection.
-    df.registerTempTable("records")
+    df.createOrReplaceTempView("records")
 
     // Once tables have been registered, you can run SQL queries over them.
     println("Result of SELECT *:")
@@ -67,7 +67,7 @@ object RDDRelation {
     parquetFile.where($"key" === 1).select($"value".as("a")).collect().foreach(println)
 
     // These files can also be registered as tables.
-    parquetFile.registerTempTable("parquetFile")
+    parquetFile.createOrReplaceTempView("parquetFile")
     spark.sql("SELECT * FROM parquetFile").collect().foreach(println)
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
index 9aba4a05a8..688c5b23c2 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
@@ -67,7 +67,7 @@ object SqlNetworkWordCount {
       val wordsDataFrame = rdd.map(w => Record(w)).toDF()
 
       // Register as table
-      wordsDataFrame.registerTempTable("words")
+      wordsDataFrame.createOrReplaceTempView("words")
 
       // Do word count on table using SQL and print it
       val wordCountsDataFrame =