Repository: spark Updated Branches: refs/heads/master 46462ff25 -> a7f903902
[DOCS] Fix typo in API for custom InputFormats based on the ânewâ MapReduce API This looks like a simple typo ```SparkContext.newHadoopRDD``` instead of ```SparkContext.newAPIHadoopRDD``` as in actual http://spark.apache.org/docs/1.2.1/api/scala/index.html#org.apache.spark.SparkContext Author: Alexander <abezzu...@nflabs.com> Closes #4718 from bzz/hadoop-InputFormats-doc-fix and squashes the following commits: 680a4c4 [Alexander] Fix typo in docs on custom Hadoop InputFormats Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/a7f90390 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/a7f90390 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/a7f90390 Branch: refs/heads/master Commit: a7f90390251ff62a0e10edf4c2eb876538597791 Parents: 46462ff Author: Alexander <abezzu...@nflabs.com> Authored: Sun Feb 22 08:53:05 2015 +0000 Committer: Sean Owen <so...@cloudera.com> Committed: Sun Feb 22 08:53:05 2015 +0000 ---------------------------------------------------------------------- docs/programming-guide.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/a7f90390/docs/programming-guide.md ---------------------------------------------------------------------- diff --git a/docs/programming-guide.md b/docs/programming-guide.md index 4e4af76..7b07018 100644 --- a/docs/programming-guide.md +++ b/docs/programming-guide.md @@ -335,7 +335,7 @@ Apart from text files, Spark's Scala API also supports several other data format * For [SequenceFiles](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/mapred/SequenceFileInputFormat.html), use SparkContext's `sequenceFile[K, V]` method where `K` and `V` are the types of key and values in the file. These should be subclasses of Hadoop's [Writable](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/Writable.html) interface, like [IntWritable](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/IntWritable.html) and [Text](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/Text.html). In addition, Spark allows you to specify native types for a few common Writables; for example, `sequenceFile[Int, String]` will automatically read IntWritables and Texts. -* For other Hadoop InputFormats, you can use the `SparkContext.hadoopRDD` method, which takes an arbitrary `JobConf` and input format class, key class and value class. Set these the same way you would for a Hadoop job with your input source. You can also use `SparkContext.newHadoopRDD` for InputFormats based on the "new" MapReduce API (`org.apache.hadoop.mapreduce`). +* For other Hadoop InputFormats, you can use the `SparkContext.hadoopRDD` method, which takes an arbitrary `JobConf` and input format class, key class and value class. Set these the same way you would for a Hadoop job with your input source. You can also use `SparkContext.newAPIHadoopRDD` for InputFormats based on the "new" MapReduce API (`org.apache.hadoop.mapreduce`). * `RDD.saveAsObjectFile` and `SparkContext.objectFile` support saving an RDD in a simple format consisting of serialized Java objects. While this is not as efficient as specialized formats like Avro, it offers an easy way to save any RDD. @@ -367,7 +367,7 @@ Apart from text files, Spark's Java API also supports several other data formats * For [SequenceFiles](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/mapred/SequenceFileInputFormat.html), use SparkContext's `sequenceFile[K, V]` method where `K` and `V` are the types of key and values in the file. These should be subclasses of Hadoop's [Writable](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/Writable.html) interface, like [IntWritable](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/IntWritable.html) and [Text](http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/Text.html). -* For other Hadoop InputFormats, you can use the `JavaSparkContext.hadoopRDD` method, which takes an arbitrary `JobConf` and input format class, key class and value class. Set these the same way you would for a Hadoop job with your input source. You can also use `JavaSparkContext.newHadoopRDD` for InputFormats based on the "new" MapReduce API (`org.apache.hadoop.mapreduce`). +* For other Hadoop InputFormats, you can use the `JavaSparkContext.hadoopRDD` method, which takes an arbitrary `JobConf` and input format class, key class and value class. Set these the same way you would for a Hadoop job with your input source. You can also use `JavaSparkContext.newAPIHadoopRDD` for InputFormats based on the "new" MapReduce API (`org.apache.hadoop.mapreduce`). * `JavaRDD.saveAsObjectFile` and `JavaSparkContext.objectFile` support saving an RDD in a simple format consisting of serialized Java objects. While this is not as efficient as specialized formats like Avro, it offers an easy way to save any RDD. --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org