This is the first release to support Scala 2.9 in addition to 2.8. Future releases are likely to be 2.9-only unless there is high demand for 2.8.
You can now save distributed datasets to the Hadoop filesystem (HDFS), Amazon S3, Hypertable, and any other storage system supported by Hadoop. There are convenience methods for several common formats, like text files and SequenceFiles. For example, to save a dataset as text:
In working with SequenceFiles, which store objects that implement Hadoop’s Writable interface, Spark will now let you use native types for certain common Writable types, like IntWritable and Text. For example:
Similarly, you can save datasets of basic types directly as SequenceFiles:
Spark now fetches dependencies via Maven and can publish Maven artifacts for easier dependency management.
This release includes broadcast and shuffle algorithms from this paper to better support applications that communicate large amounts of data.
The new SparkContext.hadoopRDD method allows reading data from Hadoop-compatible storage systems other than file systems, such as HBase, Hypertable, etc.