On Thu, Mar 2, 2017 at 12:35 PM, Gopal Vijayaraghavan <gop...@apache.org> wrote:
> > > Had the original Spark proposal implied they wished to fork portions of > the hive > > code base, I would have considered it a hostile fork. (this is open to > interpretation). > > FYI, I did ask bluntly whether Spark intends to cut-paste Hive code into > their repos previously & got an affirmative answer from rxin. > > http://grokbase.com/t/hive/dev/15cjb3kjvn/using-the-hive- > sql-parser-in-spark > > > People have the right to fork it via the licence. We can not stop that. > > Later, I did get a response that they never made a release with the said > copy-paste & they deprecated the "HiveContext" object in Spark 2.0. > > > than what Hive could handle at peak." > > > > (EC Note: How is this statement verifiable?) > > Reading about Hive at Facebook, I feel like we've already solved those > problems that were due to FB Corona + Hadoop-1 (or, 0.20 *shudder*) > limitations. > > Spark does not need be limited by Corona and the version of Hive being > compared might not have YARN or Tez on its side. > > Cheers, > Gopal > > On 3/2/17, 8:25 PM, "Edward Capriolo" <edlinuxg...@gmail.com> wrote: > > All, > > I have compiled a short (non exhaustive) list of items related to > Spark's > forking of Apache Hive code and usage of Apache Hive trademarks. > > 1) > ---------------------------- > The original spark proposal repeatedly claims that Spark "inter > operates" > with hive. > > https://wiki.apache.org/incubator/SparkProposal > > "Finally, Shark (a higher layer framework built on Spark) > inter-operates > with Apache Hive." > > (EC note: Originally spark may have linked to hive, but now the > situation > is much different.) > ------------------------- > > 2) > ------------------ > Spark distributes jar files to maven repositories carrying the hive > name. > > https://mvnrepository.com/artifact/org.spark-project.hive/hive-exec > > (EC note These are not simple "ports" features are > added/missing/broken in > artifacts named "hive") > ----------------------- > > 3) > --------------------------------- > Spark carries forked and modified copies of hive source code > > https://github.com/apache/spark/blob/39e2bad6a866d27c3ca594d15e574a > 1da3ee84cc/sql/hive-thriftserver/src/main/java/ > org/apache/hive/service/cli/session/HiveSessionHookContextImpl.java > -------------------------------------------- > > 4 > ------------------------------- > Spark has "imported" and modified components of hive > > > https://issues.apache.org/jira/browse/SPARK-12572 > > (EC note: Further discussions of the code make little no reference to > it's > origins in propaganda) > --------------------------------------------- > > 5 > -------------------------------- > Databricks, a company heaving involved in spark development, uses the > Hive > trademark to make claims > > https://databricks.com/blog/2017/01/30/integrating- > central-hive-metastore-apache-spark-databricks.html > > "The Databricks platform provides a fully managed Hive Metastore that > allows users to share a data catalog across multiple Spark clusters." > > > This blog defining hadoop (draft) is clear on this: > https://wiki.apache.org/hadoop/Defining%20Hadoop > > "Products that are derivative works of Apache Hadoop are not Apache > Hadoop, > and may not call themselves versions of Apache Hadoop, nor > Distributions of > Apache Hadoop." > > -------------------- > > 6 > ---------------------- > https://databricks.com/blog/2017/01/30/integrating- > central-hive-metastore-apache-spark-databricks.html > > "Apache Spark supports multiple versions of Hive, from 0.12 up to > 1.2.1. " > > Apache spark can NOT support multiple versions of Hive because they are > working with a fork, and there is no standard body for "supporting > hive" > > Some products have been released that have been described as > "compatible" > with Hadoop, even though parts of the Hadoop codebase have either been > changed or replaced. The Apache™ Hadoop® developer team are not a > standards > body: they do not qualify such (derivative) works as compatible. Nor do > they feel constrained by the requirements of external entities when > changing the behavior of Apache Hadoop software or related Apache > software. > ----------------------- > > 7 > --------------------------------- > The spark committers openly use the word "take" during the process of > "importing" hive code. > > https://github.com/apache/spark/pull/10583/files > "are there unit tests from Hive that we can take?" > > Apache foundation will not take a hostile fork for a proposal. Had the > original Spark proposal implied they wished to fork portions of the > hive > code base, I would have considered it a hostile fork. (this is open to > interpretation). > > (EC Note: Is this the Apache way? How can we build communities? How > would > small projects feel if for example hive "imported" copying code while > they > sat in incubation) > ------------------------------ > > 8 > ---------------------------- > Databricks (after borrowing slabs of hive code, using our trademarks, > etc) > makes disparaging comments about the performance of hive. > > https://databricks.com/blog/2017/02/28/voice-facebook- > using-apache-spark-large-scale-language-model-training.html > > "Spark-based pipelines can scale comfortably to process many times more > input data than what Hive could handle at peak. " > > (EC Note: How is this statement verifiable?) > ----------------------------------------------- > > 9 > -------------------------- > https://issues.apache.org/jira/browse/SPARK-10793 > > It's easily enough added, to the code, there's just the risk of the > fork > diverging more from ASF hive. > > (EC Note Even those responsible for this admit the code is diverging > and > will diverge more from there actions.) > ------------------------ > > 10 > ---------------------- > > My opinion of all of this: > The above points are hurtful to Hive.First, we are robbed of community. > People could be improving hive by making it more modular, but instead > they > are improving Spark's fork of hive. Next, our code base is subject to > continued "poaching". Apache Spark "imports", copies, alter, and claim > compatibility with/from Hive (I pointed out above why the compatibility > claims should not be made). Finally, We are subject to unfair > performance > comparisons "x is faster then hive", by software (spark) that is > essentially > > *POWERED BY Hive (via the forking and code copying). * > > Hive has always been a bullseye as the best hadoop SQL > https://vision.cloudera.com/impala-v-hive/ > > In my hood we have a saying, "Haters gonna hate" > > For every Impala and every Spark claiming to be better then hive, > there is > 10 HadoopDB's that collapsed under the weight of themselves. We > outlasted > fleets of them. > > That being said, software like Hive Metastore our baby. It is our TM. > It is > our creation. It is what makes us special. People have the right to > fork it > via the licence. We can not stop that. But it cant be both ways: either > downstream needs to bring in our published artifacts, or they fork and > give > what they are doing another name. > > None of this activity represents what I believe is the "Apache Way". I > believe the Apache Way would be to communicate to us, the hive > community, > about ways to make the components more modular and easier to use in > other > projects. Users suffer when the same code "moves" between two projects > there is fragmentation and typically it leads to negative effects for > both > projects. > > > -------------------------------------- > > Thanks, > Edward > > > > > Thank you for replying. http://grokbase.com/t/hive/dev/15cjb3kjvn/using-the-hive-sql-parser-in-spark "Under the Apache license, there's no actual restriction against a hostile embrace-extend by copying hive's code verbatim as long as the fork retains license notices." There is a difference between managing a project "Apache Way" and what is ultimately allowable via an Apache Licence. This exchange highlights the problem. They justify by citing no restriction on embrace-extend. However: "We do have a pretty comprehensive suite of Hive compatibility tests (by using the Hive tests directly) to ensure SQL compatibility with Hive" https://wiki.apache.org/hadoop/Defining%20Hadoop Some products have been released that have been described as "compatible" with Hadoop, even though parts of the Hadoop codebase have either been changed or replaced. The Apache™ Hadoop® developer team are not a standards body: they do not qualify such (derivative) works as compatible. Nor do they feel constrained by the requirements of external entities when changing the behavior of Apache Hadoop software or related Apache software. They assert "compatability" via their own "pretty comprehensive" suite. This is not a one off statement. I pointed this out in points 5 and 6 above. It happens repeatedly, when convenient "Hive compatbility" is asserted both on Apache lists and in marketing materials.
