Re: [DISCUSS] Spark's fork of hive

2017-03-03 Thread Edward Capriolo 
On Thu, Mar 2, 2017 at 2:08 PM, Alan Gates  wrote:

> I think the issues you point out fall into a couple of different buckets:
>
> 1) Spark forking Hive code.  As you point out, based on the license,
> there's nothing wrong with this (see naming concerns below).  I agree it's
> crappy technical practice because in the long term Hive and Spark will
> diverge and the Spark community will either give up on interoperability or
> spend more and more time maintaining it.  But if their MO is "we take the
> best of whatever you write and include it in Spark", then I think all we
> can do about it is 1) remember that imitation is the sincerest form of
> flattery; and 2) see what of there's we can incorporate into Hive.
>
> 2) I agree that they should not call Hive what they incorporate into
> Spark.  In particular shipping maven jars with org.apache.hive that do not
> contain the same functionality as ours seems problematic.  IIRC the Hive
> community raised concerns about this before with the Spark community.  I
> don't recall the outcome.  But it would make sense to me to approach the
> Spark community and ask that they not do this.
>
> As for them dissing on us in benchmarks, we all know you can set up Hive
> to run like mule (use MR on text files) and people do it all the time to
> make their stuff look good.  I'm not sure what to do about that other than
> publish our own benchmarks showing what Hive can do.
>
> Alan.
>
> > On Mar 2, 2017, at 6:55 AM, Edward Capriolo 
> 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.
> >
> >

Re: [DISCUSS] Spark's fork of hive

2017-03-02 Thread Alan Gates 
I think the issues you point out fall into a couple of different buckets:

1) Spark forking Hive code.  As you point out, based on the license, there's 
nothing wrong with this (see naming concerns below).  I agree it's crappy 
technical practice because in the long term Hive and Spark will diverge and the 
Spark community will either give up on interoperability or spend more and more 
time maintaining it.  But if their MO is "we take the best of whatever you 
write and include it in Spark", then I think all we can do about it is 1) 
remember that imitation is the sincerest form of flattery; and 2) see what of 
there's we can incorporate into Hive.

2) I agree that they should not call Hive what they incorporate into Spark.  In 
particular shipping maven jars with org.apache.hive that do not contain the 
same functionality as ours seems problematic.  IIRC the Hive community raised 
concerns about this before with the Spark community.  I don't recall the 
outcome.  But it would make sense to me to approach the Spark community and ask 
that they not do this.

As for them dissing on us in benchmarks, we all know you can set up Hive to run 
like mule (use MR on text files) and people do it all the time to make their 
stuff look good.  I'm not sure what to do about that other than publish our own 
benchmarks showing what Hive can do.

Alan.

> On Mar 2, 2017, at 6:55 AM, Edward Capriolo  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/39e2bad6a866d27c3ca594d15e574a1da3ee84cc/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
>

Re: [DISCUSS] Spark's fork of hive

2017-03-02 Thread Edward Capriolo 
On Thu, Mar 2, 2017 at 12:35 PM, Gopal Vijayaraghavan 
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"  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

Re: [DISCUSS] Spark's fork of hive

2017-03-02 Thread Gopal Vijayaraghavan 

> 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"  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/39e2bad6a866d27c3ca594d15e574a1da3ee84cc/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

[DISCUSS] Spark's fork of hive

2017-03-02 Thread Edward Capriolo 
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/39e2bad6a866d27c3ca594d15e574a1da3ee84cc/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