From d305e686b3d73213784bd75cdad7d168b22a1dc4 Mon Sep 17 00:00:00 2001
From: Olivier Girardot <o.girardot@lateral-thoughts.com>
Date: Fri, 17 Apr 2015 16:23:10 -0500
Subject: [PATCH] SPARK-6988 : Fix documentation regarding DataFrames using the
Java API
This patch includes :
* adding how to use map after an sql query using javaRDD
* fixing the first few java examples that were written in Scala
Thank you for your time,
Olivier.
Author: Olivier Girardot <o.girardot@lateral-thoughts.com>
Closes #5564 from ogirardot/branch-1.3 and squashes the following commits:
9f8d60e [Olivier Girardot] SPARK-6988 : Fix documentation regarding DataFrames using the Java API
(cherry picked from commit 6b528dc139da594ef2e651d84bd91fe0f738a39d)
Signed-off-by: Reynold Xin <rxin@databricks.com>
---
docs/sql-programming-guide.md | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 03500867df..d49233714a 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -193,8 +193,8 @@ df.groupBy("age").count().show()
<div data-lang="java" markdown="1">
{% highlight java %}
-val sc: JavaSparkContext // An existing SparkContext.
-val sqlContext = new org.apache.spark.sql.SQLContext(sc)
+JavaSparkContext sc // An existing SparkContext.
+SQLContext sqlContext = new org.apache.spark.sql.SQLContext(sc)
// Create the DataFrame
DataFrame df = sqlContext.jsonFile("examples/src/main/resources/people.json");
@@ -308,8 +308,8 @@ val df = sqlContext.sql("SELECT * FROM table")
<div data-lang="java" markdown="1">
{% highlight java %}
-val sqlContext = ... // An existing SQLContext
-val df = sqlContext.sql("SELECT * FROM table")
+SQLContext sqlContext = ... // An existing SQLContext
+DataFrame df = sqlContext.sql("SELECT * FROM table")
{% endhighlight %}
</div>
@@ -435,7 +435,7 @@ DataFrame teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AN
// The results of SQL queries are DataFrames and support all the normal RDD operations.
// The columns of a row in the result can be accessed by ordinal.
-List<String> teenagerNames = teenagers.map(new Function<Row, String>() {
+List<String> teenagerNames = teenagers.javaRDD().map(new Function<Row, String>() {
public String call(Row row) {
return "Name: " + row.getString(0);
}
@@ -599,7 +599,7 @@ DataFrame results = sqlContext.sql("SELECT name FROM people");
// The results of SQL queries are DataFrames and support all the normal RDD operations.
// The columns of a row in the result can be accessed by ordinal.
-List<String> names = results.map(new Function<Row, String>() {
+List<String> names = results.javaRDD().map(new Function<Row, String>() {
public String call(Row row) {
return "Name: " + row.getString(0);
}
@@ -860,7 +860,7 @@ DataFrame parquetFile = sqlContext.parquetFile("people.parquet");
//Parquet files can also be registered as tables and then used in SQL statements.
parquetFile.registerTempTable("parquetFile");
DataFrame teenagers = sqlContext.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19");
-List<String> teenagerNames = teenagers.map(new Function<Row, String>() {
+List<String> teenagerNames = teenagers.javaRDD().map(new Function<Row, String>() {
public String call(Row row) {
return "Name: " + row.getString(0);
}
--
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