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SPARK-6988 : Fix documentation regarding DataFrames using the Java API

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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>
This commit is contained in:
Olivier Girardot 2015-04-17 16:23:10 -05:00 committed by Reynold Xin
parent 59e206deb7
commit d305e686b3
1 changed files with 7 additions and 7 deletions
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14
docs/sql-programming-guide.md
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@ -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);
}