Re: Spark 1.0.0 - Java 8
With respect to virtual hosts, my team uses Vagrant/Virtualbox. We have 3 CentOS VMs with 4 GB RAM each - 2 worker nodes and a master node. Everything works fine, though if you are using MapR, you have to make sure they are all on the same subnet. -Suren On Fri, May 30, 2014 at 12:20 PM, Upender Nimbekar upent...@gmail.com wrote: Great News ! I've been awaiting this release to start doing some coding with Spark using Java 8. Can I run Spark 1.0 examples on a virtual host with 16 GB ram and fair descent amount of hard disk ? Or do I reaaly need to use a cluster of machines. Second, are there any good exmaples of using MLIB on Spark. Please shoot me in the right direction. Thanks Upender On Fri, May 30, 2014 at 6:12 AM, Patrick Wendell pwend...@gmail.com wrote: I'm thrilled to announce the availability of Spark 1.0.0! Spark 1.0.0 is a milestone release as the first in the 1.0 line of releases, providing API stability for Spark's core interfaces. Spark 1.0.0 is Spark's largest release ever, with contributions from 117 developers. I'd like to thank everyone involved in this release - it was truly a community effort with fixes, features, and optimizations contributed from dozens of organizations. This release expands Spark's standard libraries, introducing a new SQL package (SparkSQL) which lets users integrate SQL queries into existing Spark workflows. MLlib, Spark's machine learning library, is expanded with sparse vector support and several new algorithms. The GraphX and Streaming libraries also introduce new features and optimizations. Spark's core engine adds support for secured YARN clusters, a unified tool for submitting Spark applications, and several performance and stability improvements. Finally, Spark adds support for Java 8 lambda syntax and improves coverage of the Java and Python API's. Those features only scratch the surface - check out the release notes here: http://spark.apache.org/releases/spark-release-1-0-0.html Note that since release artifacts were posted recently, certain mirrors may not have working downloads for a few hours. - Patrick -- SUREN HIRAMAN, VP TECHNOLOGY Velos Accelerating Machine Learning 440 NINTH AVENUE, 11TH FLOOR NEW YORK, NY 10001 O: (917) 525-2466 ext. 105 F: 646.349.4063 E: suren.hiraman@v suren.hira...@sociocast.comelos.io W: www.velos.io
Re: Spark 1.0.0 - Java 8
Also, the Spark examples can run out of the box on a single machine, as well as a cluster. See the Master URLs heading here: http://spark.apache.org/docs/latest/submitting-applications.html#master-urls On Fri, May 30, 2014 at 9:24 AM, Surendranauth Hiraman suren.hira...@velos.io wrote: With respect to virtual hosts, my team uses Vagrant/Virtualbox. We have 3 CentOS VMs with 4 GB RAM each - 2 worker nodes and a master node. Everything works fine, though if you are using MapR, you have to make sure they are all on the same subnet. -Suren On Fri, May 30, 2014 at 12:20 PM, Upender Nimbekar upent...@gmail.com wrote: Great News ! I've been awaiting this release to start doing some coding with Spark using Java 8. Can I run Spark 1.0 examples on a virtual host with 16 GB ram and fair descent amount of hard disk ? Or do I reaaly need to use a cluster of machines. Second, are there any good exmaples of using MLIB on Spark. Please shoot me in the right direction. Thanks Upender On Fri, May 30, 2014 at 6:12 AM, Patrick Wendell pwend...@gmail.com wrote: I'm thrilled to announce the availability of Spark 1.0.0! Spark 1.0.0 is a milestone release as the first in the 1.0 line of releases, providing API stability for Spark's core interfaces. Spark 1.0.0 is Spark's largest release ever, with contributions from 117 developers. I'd like to thank everyone involved in this release - it was truly a community effort with fixes, features, and optimizations contributed from dozens of organizations. This release expands Spark's standard libraries, introducing a new SQL package (SparkSQL) which lets users integrate SQL queries into existing Spark workflows. MLlib, Spark's machine learning library, is expanded with sparse vector support and several new algorithms. The GraphX and Streaming libraries also introduce new features and optimizations. Spark's core engine adds support for secured YARN clusters, a unified tool for submitting Spark applications, and several performance and stability improvements. Finally, Spark adds support for Java 8 lambda syntax and improves coverage of the Java and Python API's. Those features only scratch the surface - check out the release notes here: http://spark.apache.org/releases/spark-release-1-0-0.html Note that since release artifacts were posted recently, certain mirrors may not have working downloads for a few hours. - Patrick -- SUREN HIRAMAN, VP TECHNOLOGY Velos Accelerating Machine Learning 440 NINTH AVENUE, 11TH FLOOR NEW YORK, NY 10001 O: (917) 525-2466 ext. 105 F: 646.349.4063 E: suren.hiraman@v suren.hira...@sociocast.comelos.io W: www.velos.io
Re: Spark and Java 8
Running Hadoop and HDFS on unsupported JVM runtime sounds a little adventurous. But as long as Spark can run in a separate Java 8 runtime it's all good. I think having lambdas and type inference is huge when writing these jobs and using Scala (paying the price of complexity, poor tooling etc etc) for this tiny feature is often not justified. On Wed, May 7, 2014 at 2:03 AM, Dean Wampler deanwamp...@gmail.com wrote: Cloudera customers will need to put pressure on them to support Java 8. They only officially supported Java 7 when Oracle stopped supporting Java 6. dean On Wed, May 7, 2014 at 5:05 AM, Matei Zaharia matei.zaha...@gmail.comwrote: Java 8 support is a feature in Spark, but vendors need to decide for themselves when they’d like support Java 8 commercially. You can still run Spark on Java 7 or 6 without taking advantage of the new features (indeed our builds are always against Java 6). Matei On May 6, 2014, at 8:59 AM, Ian O'Connell i...@ianoconnell.com wrote: I think the distinction there might be they never said they ran that code under CDH5, just that spark supports it and spark runs under CDH5. Not that you can use these features while running under CDH5. They could use mesos or the standalone scheduler to run them On Tue, May 6, 2014 at 6:16 AM, Kristoffer Sjögren sto...@gmail.comwrote: Hi I just read an article [1] about Spark, CDH5 and Java 8 but did not get exactly how Spark can run Java 8 on a YARN cluster at runtime. Is Spark using a separate JVM that run on data nodes or is it reusing the YARN JVM runtime somehow, like hadoop1? CDH5 only supports Java 7 [2] as far as I know? Cheers, -Kristoffer [1] http://blog.cloudera.com/blog/2014/04/making-apache-spark-easier-to-use-in-java-with-java-8/ [2] http://www.cloudera.com/content/cloudera-content/cloudera-docs/CDH5/latest/CDH5-Requirements-and-Supported-Versions/CDH5-Requirements-and-Supported-Versions.html -- Dean Wampler, Ph.D. Typesafe @deanwampler http://typesafe.com http://polyglotprogramming.com
Re: Spark and Java 8
Hi Kristoffer, You're correct that CDH5 only supports up to Java 7 at the moment. But Yarn apps do not run in the same JVM as Yarn itself (and I believe MR1 doesn't either), so it might be possible to pass arguments in a way that tells Yarn to launch the application master / executors with the Java 8 runtime. I have never tried this, so I don't know if it's really possible, and it's obviously not supported (also because Java 8 support is part of Spark 1.0 which hasn't been released yet). You're welcome to try it out, and if you get it to work in some manner, it would be great to hear back. On Tue, May 6, 2014 at 6:16 AM, Kristoffer Sjögren sto...@gmail.com wrote: Hi I just read an article [1] about Spark, CDH5 and Java 8 but did not get exactly how Spark can run Java 8 on a YARN cluster at runtime. Is Spark using a separate JVM that run on data nodes or is it reusing the YARN JVM runtime somehow, like hadoop1? CDH5 only supports Java 7 [2] as far as I know? Cheers, -Kristoffer [1] http://blog.cloudera.com/blog/2014/04/making-apache-spark-easier-to-use-in-java-with-java-8/ [2] http://www.cloudera.com/content/cloudera-content/cloudera-docs/CDH5/latest/CDH5-Requirements-and-Supported-Versions/CDH5-Requirements-and-Supported-Versions.html -- Marcelo
Re: Spark and Java 8
I think the distinction there might be they never said they ran that code under CDH5, just that spark supports it and spark runs under CDH5. Not that you can use these features while running under CDH5. They could use mesos or the standalone scheduler to run them On Tue, May 6, 2014 at 6:16 AM, Kristoffer Sjögren sto...@gmail.com wrote: Hi I just read an article [1] about Spark, CDH5 and Java 8 but did not get exactly how Spark can run Java 8 on a YARN cluster at runtime. Is Spark using a separate JVM that run on data nodes or is it reusing the YARN JVM runtime somehow, like hadoop1? CDH5 only supports Java 7 [2] as far as I know? Cheers, -Kristoffer [1] http://blog.cloudera.com/blog/2014/04/making-apache-spark-easier-to-use-in-java-with-java-8/ [2] http://www.cloudera.com/content/cloudera-content/cloudera-docs/CDH5/latest/CDH5-Requirements-and-Supported-Versions/CDH5-Requirements-and-Supported-Versions.html
Re: Spark and Java 8
Java 8 support is a feature in Spark, but vendors need to decide for themselves when they’d like support Java 8 commercially. You can still run Spark on Java 7 or 6 without taking advantage of the new features (indeed our builds are always against Java 6). Matei On May 6, 2014, at 8:59 AM, Ian O'Connell i...@ianoconnell.com wrote: I think the distinction there might be they never said they ran that code under CDH5, just that spark supports it and spark runs under CDH5. Not that you can use these features while running under CDH5. They could use mesos or the standalone scheduler to run them On Tue, May 6, 2014 at 6:16 AM, Kristoffer Sjögren sto...@gmail.com wrote: Hi I just read an article [1] about Spark, CDH5 and Java 8 but did not get exactly how Spark can run Java 8 on a YARN cluster at runtime. Is Spark using a separate JVM that run on data nodes or is it reusing the YARN JVM runtime somehow, like hadoop1? CDH5 only supports Java 7 [2] as far as I know? Cheers, -Kristoffer [1] http://blog.cloudera.com/blog/2014/04/making-apache-spark-easier-to-use-in-java-with-java-8/ [2] http://www.cloudera.com/content/cloudera-content/cloudera-docs/CDH5/latest/CDH5-Requirements-and-Supported-Versions/CDH5-Requirements-and-Supported-Versions.html
