Thanks. I'm fine with the logic change, although I was a bit surprised to see Hadoop used for file I/O.
Anyway, the jira issue and pull request discussions mention a flag to enable overwrites. That would be very convenient for a tutorial I'm writing, although I wouldn't recommend it for normal use, of course. However, I can't figure out if this actually exists. I found the spark.files.overwrite property, but that doesn't apply. Does this override flag, method call, or method argument actually exist? Thanks, Dean On Tue, Apr 29, 2014 at 1:54 PM, Patrick Wendell <pwend...@gmail.com> wrote: > Hi Dean, > > We always used the Hadoop libraries here to read and write local > files. In Spark 1.0 we started enforcing the rule that you can't > over-write an existing directory because it can cause > confusing/undefined behavior if multiple jobs output to the directory > (they partially clobber each other's output). > > https://issues.apache.org/jira/browse/SPARK-1100 > https://github.com/apache/spark/pull/11 > > In the JIRA I actually proposed slightly deviating from Hadoop > semantics and allowing the directory to exist if it is empty, but I > think in the end we decided to just go with the exact same semantics > as Hadoop (i.e. empty directories are a problem). > > - Patrick > > On Tue, Apr 29, 2014 at 9:43 AM, Dean Wampler <deanwamp...@gmail.com> > wrote: > > I'm observing one anomalous behavior. With the 1.0.0 libraries, it's > using > > HDFS classes for file I/O, while the same script compiled and running > with > > 0.9.1 uses only the local-mode File IO. > > > > The script is a variation of the Word Count script. Here are the "guts": > > > > object WordCount2 { > > def main(args: Array[String]) = { > > > > val sc = new SparkContext("local", "Word Count (2)") > > > > val input = sc.textFile(".../some/local/file").map(line => > > line.toLowerCase) > > input.cache > > > > val wc2 = input > > .flatMap(line => line.split("""\W+""")) > > .map(word => (word, 1)) > > .reduceByKey((count1, count2) => count1 + count2) > > > > wc2.saveAsTextFile("output/some/directory") > > > > sc.stop() > > > > It works fine compiled and executed with 0.9.1. If I recompile and run > with > > 1.0.0-RC1, where the same output directory still exists, I get this > > familiar Hadoop-ish exception: > > > > [error] (run-main-0) org.apache.hadoop.mapred.FileAlreadyExistsException: > > Output directory > > > file:/Users/deanwampler/projects/typesafe/activator/activator-spark/output/kjv-wc > > already exists > > org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory > > > file:/Users/deanwampler/projects/typesafe/activator/activator-spark/output/kjv-wc > > already exists > > at > > > org.apache.hadoop.mapred.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:121) > > at > > > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:749) > > at > > > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:662) > > at > > > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:581) > > at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1057) > > at spark.activator.WordCount2$.main(WordCount2.scala:42) > > at spark.activator.WordCount2.main(WordCount2.scala) > > ... > > > > Thoughts? > > > > > > On Tue, Apr 29, 2014 at 3:05 AM, Patrick Wendell <pwend...@gmail.com> > wrote: > > > >> Hey All, > >> > >> This is not an official vote, but I wanted to cut an RC so that people > can > >> test against the Maven artifacts, test building with their > configuration, > >> etc. We are still chasing down a few issues and updating docs, etc. > >> > >> If you have issues or bug reports for this release, please send an > e-mail > >> to the Spark dev list and/or file a JIRA. > >> > >> Commit: d636772 (v1.0.0-rc3) > >> > >> > https://git-wip-us.apache.org/repos/asf?p=spark.git;a=commit;h=d636772ea9f98e449a038567b7975b1a07de3221 > >> > >> Binaries: > >> http://people.apache.org/~pwendell/spark-1.0.0-rc3/ > >> > >> Docs: > >> http://people.apache.org/~pwendell/spark-1.0.0-rc3-docs/ > >> > >> Repository: > >> https://repository.apache.org/content/repositories/orgapachespark-1012/ > >> > >> == API Changes == > >> If you want to test building against Spark there are some minor API > >> changes. We'll get these written up for the final release but I'm > noting a > >> few here (not comprehensive): > >> > >> changes to ML vector specification: > >> > >> > http://people.apache.org/~pwendell/spark-1.0.0-rc3-docs/mllib-guide.html#from-09-to-10 > >> > >> changes to the Java API: > >> > >> > http://people.apache.org/~pwendell/spark-1.0.0-rc3-docs/java-programming-guide.html#upgrading-from-pre-10-versions-of-spark > >> > >> coGroup and related functions now return Iterable[T] instead of Seq[T] > >> ==> Call toSeq on the result to restore the old behavior > >> > >> SparkContext.jarOfClass returns Option[String] instead of Seq[String] > >> ==> Call toSeq on the result to restore old behavior > >> > >> Streaming classes have been renamed: > >> NetworkReceiver -> Receiver > >> > > > > > > > > -- > > Dean Wampler, Ph.D. > > Typesafe > > @deanwampler > > http://typesafe.com > > http://polyglotprogramming.com > -- Dean Wampler, Ph.D. Typesafe @deanwampler http://typesafe.com http://polyglotprogramming.com
