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author | Michael Armbrust <michael@databricks.com> | 2014-08-02 18:27:04 -0700 |
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committer | Michael Armbrust <michael@databricks.com> | 2014-08-02 18:27:04 -0700 |
commit | 1a8043739dc1d9435def6ea3c6341498ba52b708 (patch) | |
tree | fe499822fa58fc9416e8664b76839b4e198679a2 /docs | |
parent | d210022e96804e59e42ab902e53637e50884a9ab (diff) | |
download | spark-1a8043739dc1d9435def6ea3c6341498ba52b708.tar.gz spark-1a8043739dc1d9435def6ea3c6341498ba52b708.tar.bz2 spark-1a8043739dc1d9435def6ea3c6341498ba52b708.zip |
[SPARK-2739][SQL] Rename registerAsTable to registerTempTable
There have been user complaints that the difference between `registerAsTable` and `saveAsTable` is too subtle. This PR addresses this by renaming `registerAsTable` to `registerTempTable`, which more clearly reflects what is happening. `registerAsTable` remains, but will cause a deprecation warning.
Author: Michael Armbrust <michael@databricks.com>
Closes #1743 from marmbrus/registerTempTable and squashes the following commits:
d031348 [Michael Armbrust] Merge remote-tracking branch 'apache/master' into registerTempTable
4dff086 [Michael Armbrust] Fix .java files too
89a2f12 [Michael Armbrust] Merge remote-tracking branch 'apache/master' into registerTempTable
0b7b71e [Michael Armbrust] Rename registerAsTable to registerTempTable
Diffstat (limited to 'docs')
-rw-r--r-- | docs/sql-programming-guide.md | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 7261badd41..0465468084 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -142,7 +142,7 @@ case class Person(name: String, age: Int) // Create an RDD of Person objects and register it as a table. val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Person(p(0), p(1).trim.toInt)) -people.registerAsTable("people") +people.registerTempTable("people") // SQL statements can be run by using the sql methods provided by sqlContext. val teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19") @@ -210,7 +210,7 @@ JavaRDD<Person> people = sc.textFile("examples/src/main/resources/people.txt").m // Apply a schema to an RDD of JavaBeans and register it as a table. JavaSchemaRDD schemaPeople = sqlContext.applySchema(people, Person.class); -schemaPeople.registerAsTable("people"); +schemaPeople.registerTempTable("people"); // SQL can be run over RDDs that have been registered as tables. JavaSchemaRDD teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19") @@ -248,7 +248,7 @@ people = parts.map(lambda p: {"name": p[0], "age": int(p[1])}) # In future versions of PySpark we would like to add support for registering RDDs with other # datatypes as tables schemaPeople = sqlContext.inferSchema(people) -schemaPeople.registerAsTable("people") +schemaPeople.registerTempTable("people") # SQL can be run over SchemaRDDs that have been registered as a table. teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19") @@ -292,7 +292,7 @@ people.saveAsParquetFile("people.parquet") val parquetFile = sqlContext.parquetFile("people.parquet") //Parquet files can also be registered as tables and then used in SQL statements. -parquetFile.registerAsTable("parquetFile") +parquetFile.registerTempTable("parquetFile") val teenagers = sqlContext.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19") teenagers.map(t => "Name: " + t(0)).collect().foreach(println) {% endhighlight %} @@ -314,7 +314,7 @@ schemaPeople.saveAsParquetFile("people.parquet"); JavaSchemaRDD parquetFile = sqlContext.parquetFile("people.parquet"); //Parquet files can also be registered as tables and then used in SQL statements. -parquetFile.registerAsTable("parquetFile"); +parquetFile.registerTempTable("parquetFile"); JavaSchemaRDD teenagers = sqlContext.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19"); List<String> teenagerNames = teenagers.map(new Function<Row, String>() { public String call(Row row) { @@ -340,7 +340,7 @@ schemaPeople.saveAsParquetFile("people.parquet") parquetFile = sqlContext.parquetFile("people.parquet") # Parquet files can also be registered as tables and then used in SQL statements. -parquetFile.registerAsTable("parquetFile"); +parquetFile.registerTempTable("parquetFile"); teenagers = sqlContext.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19") teenNames = teenagers.map(lambda p: "Name: " + p.name) for teenName in teenNames.collect(): @@ -378,7 +378,7 @@ people.printSchema() // |-- name: StringType // Register this SchemaRDD as a table. -people.registerAsTable("people") +people.registerTempTable("people") // SQL statements can be run by using the sql methods provided by sqlContext. val teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19") @@ -416,7 +416,7 @@ people.printSchema(); // |-- name: StringType // Register this JavaSchemaRDD as a table. -people.registerAsTable("people"); +people.registerTempTable("people"); // SQL statements can be run by using the sql methods provided by sqlContext. JavaSchemaRDD teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19"); @@ -455,7 +455,7 @@ people.printSchema() # |-- name: StringType # Register this SchemaRDD as a table. -people.registerAsTable("people") +people.registerTempTable("people") # SQL statements can be run by using the sql methods provided by sqlContext. teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19") |