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SPARK-6988 : Fix documentation regarding DataFrames using the Java API #5564

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SPARK-6988 : Fix documentation regarding DataFrames using the Java API #5564

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14 changes: 7 additions & 7 deletions docs/sql-programming-guide.md
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Original file line number Diff line number Diff line change
Expand Up @@ -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");
Expand Down Expand Up @@ -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>

Expand Down Expand Up @@ -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);
}
Expand Down Expand Up @@ -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);
}
Expand Down Expand Up @@ -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);
}
Expand Down