Hello,
I have a couple of questions on LLAP and hive.server2.enable.doAs. I've
learned that LLAP does not support hive.server2.enable.doAs=true, but what
if we disable LLAP IO? If LLAP IO is disabled and no cache is used in LLAP
daemons, I guess it should be okay to allow
For question 1, if hive.server2.enable.doAs is set to true, the AppMaster
fails to connect to LLAP daemons (from my experiments).
--- Sungwoo
On Fri, May 18, 2018 at 1:02 AM, Sungwoo Park <glap...@gmail.com> wrote:
> Hello,
>
> I have a couple of questions on LLAP and hive.serv
Hive-MR3 could be a solution for you. It supports everything that you
mention in the previous post. I have written a blog article discussing the
pros and cons of Hive-MR3 with respect to Hive-LLAP.
https://mr3.postech.ac.kr/blog/2018/05/19/comparison-hivemr3-llap/
--- Sungwoo
On Thu, May 10,
Hello Hive users,
I am pleased to announce the release of Hive-MR3 0.2.
Hive-MR3 now supports LLAP I/O. I have published a blog article that
compares the stability and performance of Hive-MR3 and Hive-LLAP:
https://mr3.postech.ac.kr/blog/2018/05/19/comparison-hivemr3-llap/
>From the blog
iguration parameters (because I imported
hive-site.xml from Hive 2). Any suggestion would be appreciated.
Thanks a lot,
--- Sungwoo Park
This is a diff file that let me compile Hive 3.0 on Hadoop 2.8.0 (and also
run it on Hadoop 2.7.x).
diff --git a/pom.xml b/pom.xml
index c57ff58..8445288 100644
--- a/pom.xml
+++ b/pom.xml
@@ -146,7 +146,7 @@
19.0
2.4.11
1.3.166
-3.1.0
+2.8.0
/hadoop-hdfs/
> CentralizedCacheManagement.html
>
> To answer your original question: why not implement the whole job in Hive?
> Or orchestrate using oozie some parts in mr and some in Huve.
>
> On 30. Jan 2018, at 05:15, Sungwoo Park <glap...@gmail.com> wrote:
>
> Hello all,
>
>
Hello all,
I wonder if an external YARN container can send requests to LLAP daemon to
read data from its in-memory cache. For example, YARN containers owned by a
typical MapReduce job (e.g., TeraSort) could fetch data directly from LLAP
instead of contacting HDFS. In this scenario, LLAP daemon
The article can be found at:
https://mr3.postech.ac.kr/blog/2018/08/15/comparison-llap-presto-spark-mr3/
-- Sungwoo Park
On Thu, Aug 16, 2018 at 10:53 PM, Sungwoo Park wrote:
> Hello Hive users,
>
> I am pleased to announce the release of MR3 0.3. A new feature of MR3 0.3
> is
0.203e
3) Spark 2.2.0 included in HDP 2.6.4
4) Hive 3.0.0 on Tez
5) Hive 3.0.0 on MR3
6) Hive 2.3.3 on MR3
You can download MR3 0.3 at:
https://mr3.postech.ac.kr/download/home/
Thank you for your interest!
--- Sungwoo Park
not affect DAG generation.
This issue is not related to query reexecution, as even with query
reexecution disabled (hive.query.reexecution.enabled set to false), I still
see this problem occurring.
--- Sungwoo Park
On Fri, Jul 13, 2018 at 4:48 PM, Zoltan Haindrich wrote:
> Hello Sungwoo!
&g
i Sungwoo，
>
> Just want to confirm, does that mean I just need to update the hive
> version, without updating the hadoop version?
>
> Thanks!
>
> Best,
> Zhefu Peng
>
>
> ------ 原始邮件 --
> *发件人:* "Sungwoo Park";
> *发送时间:* 201
previously posted a diff file that lets us compile Hadoop 3.x on Hadoop
2.8+.
http://mail-archives.apache.org/mod_mbox/hive-user/201806.mbox/%3CCAKHFPXDDFn52buKetHzSXTtjzX3UMHf%3DQvxm9QNNkv9r5xBs-Q%40mail.gmail.com%3E
--- Sungwoo Park
On Thu, Jul 19, 2018 at 8:21 PM, 彭鱼宴 <461292...@qq.com>
Hello Gopal,
I have been looking further into this issue, and have found that the
non-determinstic behavior of Hive in
generating DAGs is actually due to the logic in
AggregateStatsCache.findBestMatch() called from
AggregateStatsCache.get(), as well as the disproportionate distribution of
Nulls
at 10:55:19PM +0900, Sungwoo Park wrote:
> > The article compare the following six systems:
>
> Great article, as usual. Would have been great to also compare
> concurrent queries. In particular, I guess presto on that point perform
> the best. That metric is major since su
ome internal configuration key in HiveConf that
enables/disables some optimization depending on the accumulate statistics
in HiveServer2? (I haven't tested it yet, but I can also test with Hive
2.x.)
Thank you in advance,
--- Sungwoo Park
of
ApplicationMaster in MR3. In particular, it makes a better utilization of
computing resources and thus yields a higher throughput for concurrent
queries.
--- Sungwoo Park
rs between the AMs.
>
> On Wed, Apr 4, 2018 at 10:06 AM Sungwoo Park <glap...@gmail.com> wrote:
>
>> Hello Hive users,
>>
>> I am pleased to announce MR3 and Hive-MR3. Please visit the following
>> webpage for everything on MR3 and Hive-MR3:
>>
>> https://m
there is no
launch cost. Containers are also shared by all queries and thus run like
daemons.
https://mr3.postech.ac.kr/hivemr3/features/hiveserver2/
Hive-MR3 0.1 does not support LLAP IO yet, but Hive-MR3 0.2 will support
LLAP IO (which will be released by the end of this month.)
--- Sungwoo Park
On Mon
this NPE.
--- Sungwoo Park
On Wed, Mar 21, 2018 at 9:24 AM, Anuj Lal <a...@lendingclub.com> wrote:
>
>
>
> We are also facing the issue as described in
>
> https://issues.apache.org/jira/browse/HIVE-18786?page=
> com.atlassian.jira.plugin.system.issuetabpanels%3Aal
/31/performance-evaluation-0.4/
You can download MR3 0.4 at:
https://mr3.postech.ac.kr/download/home/
--- Sungwoo Park
I am pleased to announce the release of MR3 0.6. New key features are:
- In Hive on Kubernetes, DAGAppMaster can run in its own Pod.
- MR3-UI requires only Timeline Server.
- Hive on MR3 is much more stable because it supports memory monitoring
when loading hash tables for Map-side join.
You can
also supports Hive 3.1.1 and Hive 2.3.4.
You can download MR3 0.5 at:
https://mr3.postech.ac.kr/download/home/
--- Sungwoo Park
/performance-evaluation-0.4/
--- Sungwoo Park
On Mon, Apr 15, 2019 at 8:44 PM Artur Sukhenko
wrote:
> Hi,
> We are using CDH 5, with Impala 2.7.0-cdh5.9.1 and Hive 1.1 (MapReduce)
> I can't find the info regarding Hive on Tez performance compared to Impala.
> Does someone know or compared it
an FAQ page:
https://mr3.postech.ac.kr/faq/home/
You can download MR3 0.7 at:
https://mr3.postech.ac.kr/download/home/
--- Sungwoo Park
at 7:56 PM Sungwoo Park wrote:
> I am pleased to announce the release of MR3 0.8. New features are:
>
> -- Hive on MR3 on Yarn fully supports recovery:
> https://mr3.postech.ac.kr/hivemr3/features/recovery/
>
> -- Hive on MR3 on Yarn supports high availability in which mult
ger.
Hive on Kubernetes supports Timeline Server.
You can download MR3 0.8 at:
https://mr3.postech.ac.kr/download/home/
--- Sungwoo Park
I have published a new article on the correctness of Hive on MR3, Presto,
and Impala:
https://mr3.postech.ac.kr/blog/2019/06/26/correctness-hivemr3-presto-impala/
Hope you enjoy reading the article.
--- Sungwoo
e columns in the result set and conduct a large diff on them?
>
> On Wednesday, June 26, 2019, Sungwoo Park wrote:
>
>> I have published a new article on the correctness of Hive on MR3, Presto,
>> and Impala:
>>
>>
>> https://mr3.postech.ac.kr/blog/2019/06/26/c
Not solution to the problem on HDP 2.6.5, but I have tested the first
script in Hive 2.3.4 and Hive 3.1.1. On Hive 2.3.4, it returns 1 row, and
on Hive 3.1.1, it returns no row. So, I guess the bug is still in HDP 2.6.5.
--- Sungwoo
On Tue, Apr 23, 2019 at 7:40 PM Rajat Khandelwal wrote:
> Hi
Hello Hive users,
I have published a new article that compares Presto 317 and Hive 3.1.1 on
MR3 0.10 (snapshot).
https://mr3.postech.ac.kr/blog/2019/08/22/comparison-presto317-0.10/
I haven't tested myself, but I guess Hive-LLAP also runs much faster than
Presto.
--- Sungwoo
Not a solution, but one can use \n in the search string, e.g.:
select * from default.withdraw where id like '%withdraw\ncash';
select * from default.withdraw where id like '%withdraw%\ncash';
select * from default.withdraw where id like '%withdraw%\n%cash';
--- Sungwoo
On Tue, Jul 30, 2019 at
a serverless
environment.) https://mr3.postech.ac.kr/hivek8s/guide/multiple-metastores/
* UDFs work okay on Kubernetes.
You can download MR3 0.9 at:
https://mr3.postech.ac.kr/download/home/
--- Sungwoo Park
https://youtu.be/1NB7GtI8NXM
I have uploaded a video demonstrating Hive on Kubernetes using MR3.
--- Sungwoo
On Fri, Jun 28, 2019 at 4:44 AM Sungwoo Park wrote:
> I have created a quick start guide showing how to run Hive-MR3 on
> Kubernetes using Minikube on a single machine.
I have published a new article that compares: Hive-LLAP in HDP 3.1.4, Hive
3.1.2 on MR3 0.10, and Hive 4.0.0-SNAPSHOT on MR3 0.10. You can find the
result at:
https://mr3.postech.ac.kr/blog/2019/11/03/hive-performance-0.10/
Cheers,
--- Sungwoo
For the problem of not returning the result to the console, I think it
occurs because the default file system is set to local file system, not to
HDFS. Perhaps hive.exec.scratchdir is already set to /tmp/hive, but if the
default file system is local, FileSinkOperator writes the final result to
the
-in/out. So if you would like to try autoscaling with Hive on MR3, we
suggest EKS instead of EMR.
https://mr3.postech.ac.kr/quickstart/aws/run-eks-autoscaling/
You can download MR3 0.11 at:
https://mr3.postech.ac.kr/download/home/
Cheers,
--- Sungwoo Park
ore db.
>
> Thanks.
>
>
>
>
> On Mon, Dec 9, 2019 at 12:46 PM Sungwoo Park wrote:
>
>> Not a definitive answer, but my test result might help. I tested with
>> HiveServer2 1.2.2 and Metastore 2.3.6. Queries in the TPC-DS benchmark
>> (which only read data an
Not a definitive answer, but my test result might help. I tested with
HiveServer2 1.2.2 and Metastore 2.3.6. Queries in the TPC-DS benchmark
(which only read data and never update) run okay. Creating new tables and
loading data to tables also work okay. So, I guess for basic uses of Hive,
running
/download/home/
Cheers,
--- Sungwoo Park
://hub.docker.com/u/glaparkdocker
Cheers,
--- Sungwoo Park
I think this problem of choosing a cluster capacity is really challenging
because the desired cluster capacity depends not only on the size of the
dataset but also on the complexity of queries. For example, the execution
time of the TPC-DS queries on the same dataset can range from sub-10
seconds
Not a solution, but looking at the source code of S3AFileSystem.java
(Hadoop 2.8.5), I think the Exception raised inside S3AFileSystem.rename()
is swallowed and only a new HiveException is reported. So, in order to find
out the root cause, I guess you might need to set Log level to DEBUG and
see
be useful to those interested in trying MR3 in
production.
https://www.datamonad.com/post/2020-02-19-testing-mr3/
Cheers,
--- Sungwoo Park
I tested the example on Hive 2.3.6, and it returned correct results. Hive
3.1.2 and 4.0.0-SNAPSHOT also returned correct results. So, I guess, if
this is a bug, it was introduced somewhere around Hive 3.0 and fixed in
3.1.2.
On Hive 2.3.6, I used these commands instead:
create table dummy(a
nworks/spark/sql/hive/llap/HiveWarehouseDataSourceReader.java
>
> That being said, I'm not sure if this UDF is technically supported as a
> public API by the Hive community, so you may want to check about that.
>
> Eric
>
> On Sun, Apr 5, 2020 at 11:52 AM Sungwoo Park wrot
Hello,
I would like to learn the use of UDF get_splits(). I tried such queries as:
select get_splits("select * from web_returns", 1) ;
select get_splits("select count(*) from web_returns", 1);
These queries just return InputSplit objects, and I would like to see an
example that uses the result
I have tested the script with Hive 2.3.6, Hive 3.1.2, and Hive
4.0.0-SNAPSHOT (all with minor modifications), and have not found any
problem. So, I guess all the master branches are fine.
If Hive 3.0.0.3.1 is the release included in HDP 3.0.0 or HDP 3.0.1, I
remember that this Hive-LLAP/Tez
Hi,
I have a question on the consistency between data (e.g., on HDFS) and
metadata kept by Metastore before and after compaction.
Here is a scenario:
1. We back up the database for Metastore (before performing compaction).
2. We perform compaction.
3. After performing compaction, we lose the
Hi everyone,
We created a video demo of fault tolerance in Hive on MR3 on Kubernetes,
using Hive 3.1.2 and MR3 1.1. Hope you enjoy it!
https://youtu.be/uoZGsMUlhew
Cheers,
--- Sungwoo
Hello,
We use just TCP readiness/liveness probes checking the Metastore listener
port (specified by hive.metastore.port or metastore.thrift.port). I don't
know if an HTTP endpoint is available for Metastore.
readinessProbe:
tcpSocket:
port: 9083
We are pleased to announce the release of MR3 1.1. Three main improvements
in MR3 1.1 are:
1. Hive on MR3 on Kubernetes now runs almost as fast as Hive on MR3 on
Hadoop. For experimental results, please see a new blog article "Why you
should run Hive on Kubernetes, even in a Hadoop cluster".
Hello Hive users,
MR3 1.2 has been released. A few improvements in this release are:
1. MR3 can publish Prometheus metrics.
2. On Kubernetes, the user can change the total resources for workers
dynamically (e.g., by using Prometheus metrics). This feature can be
combined with autoscaling in
Hi Peter,
- Are these patches you mention below bugfixes, or new features on Hive
> 3.1.3? (This might be a typo as I think the last Hive release is 3.1.2)
>
They are a collection of bug-fixes and improvements picked up from
master/branch-3 branches. The list is mostly based on the additional
. (You can ignore the last commit which is internal to our
work.)
https://github.com/mr3project/hive-mr3/commits/master3
Thanks,
--- Sungwoo Park
We are pleased to announce the release of MR3 1.3.
Highlights in this release are:
1) MR3
On both Hadoop and Kubernetes, there is no limit on the aggregate memory of
ContainerWorkers, so MR3 can run in a cluster of any size.
2) Hive on MR3
We have backported about 350 patches to Apache Hive
Hello,
Hive PMC members or committers could share insider knowledge about the
status of the Hive project, but here is my impression on Hive 3.1.2 as an
outsider.
Hive 3.1.2 is widely used in production, but not maintained seriously. (You
could just check out the # of commits in branch-3.1 for
Hello Hive users,
We have updated the repository that backports patches to Hive 3.1.2. Now it
backports about 350 patches from the master branch to branch-3.1 of
November 2020. You can ignore the last two commits which add MR3 backend
and remove Hive on Spark.
Hi,
For 1, Hive 3.1.2 has a bug which leaks Metastore connections. This was
reported in HIVE-20600:
https://issues.apache.org/jira/browse/HIVE-20600
You might reproduce the bug by inserting values into a table and checking
the number of connections, e.g.:
0: jdbc:hive2://blue0:9852/> CREATE
Actually we can run Hive 3.1.2 with Ranger!
To run Hive 3.1.2 with Ranger 2.0.0, you could set:
hive.security.authorization.enabled=true
hive.security.authenticator.manager=org.apache.hadoop.hive.ql.security.SessionStateUserAuthenticator
Sorry, I missed one thing -- you need to backport:
HIVE-20344: PrivilegeSynchronizer for SBA might hit AccessControlException
(Daniel Dai, reviewed by Vaibhav Gumashta)
--- Sungwoo
On Wed, Sep 22, 2021 at 12:24 AM Sungwoo Park wrote:
> Actually we can run Hive 3.1.2 with Ranger!
>
&g
Up to MR3 version 1.2, Hive-MR3 supported Hive 3.1.2 on Hadoop 2.7+. From
MR3 version 1.3 on, we did not release distributions for Hadoop 2.7+
because all use cases in production were using Hadoop 3+. (However it's
still easy for us to build a distribution for Hadoop 2.7+.)
When we were
My understanding is that additional calls to S3 APi is the price to pay for
using the Hadoop library which only emulates FileSystem on top of S3. S3 is
not a distributed file system like HDFS, so some of the API calls cannot be
optimized in an ideal way.
For (i), a more serious problem is the
We are pleased to announce MR3 1.4 and MR3 App.
1.
We have backported over 600 patches to Apache Hive 3.1.
https://github.com/mr3project/hive-mr3
This repository is maintained as part of developing Hive on MR3, but can
also be used for building Apache Hive (by ignoring the last two commits).
Hi Hive users,
Here is our latest article on the performance of Spark 2, Spark 3, and Hive
3. Hope you find it interesting.
https://www.datamonad.com/post/2022-04-01-spark-hive-performance-1.4/
Spark 3 is catching up with Hive very fast, at least when executing
sequential queries. For
On Thu, Nov 2, 2023 at 1:43 PM Sungwoo Park wrote:
> Have you done comparison between uniffle and celeborn..?
>>
>
> We did not compare the performance of Uniffle and Celeborn (because
> Hive-MR3-Celeborn has been released but Hive-MR3-Uniffle is not complete
> yet). Much of
>
> Have you done comparison between uniffle and celeborn..?
>
We did not compare the performance of Uniffle and Celeborn (because
Hive-MR3-Celeborn has been released but Hive-MR3-Uniffle is not complete
yet). Much of the code in Hive-MR3-Celeborn is currently reused in
Hive-MR3-Uniffle, so we
future) to help compute
> engines
> > better use disaggregated architecture, as well as become more efficient
> and
> > stable for huge shuffle sized jobs.
> >
> >
> > Currently Celeborn supports Hive on MR, and I think integrating with MR3
> > provides a good example
Forwarded to user@hive as I think many people are curious about the release
of Hive 4.
-- Forwarded message -
From: Sungwoo Park
Date: Sat, Nov 4, 2023 at 12:42 AM
Subject: Release of Hive 4 and TPC-DS benchmark
To:
Hi everyone,
I would like to resume the discussion
Hi Hive users,
Before the impending release of MR3 1.8, we would like to announce the
release of Hive-MR3 with Celeborn (Hive 3.1.3 on MR3 1.8 with Celeborn
0.3.1).
Apache Celeborn [1] is remote shuffle service, similar to Magnet [2] and
Apache Uniffle [3] (which was discussed in this Hive
Hello,
For more recent benchmark results, please see [1] where we compare Trino
418, Spark 3.4.0, and Hive 3.1.3 (on MR3 1.7) using TPC-DS 10TB. Spark
takes about 19600 seconds to complete all the queries, whereas Trino and
Hive take about 7400 seconds only. The experiment does not use Hive-LLAP,
Hi Hive users,
We created MR3 Cloud, a web-based interface for executing Hive on Amazon
EKS and Kubernetes. After specifying parameters in an interactive way, the
user can download YAML files for creating an EKS cluster and Kubernetes
objects. The user can create all the following components at
we were brainstorming about the future of the Hive 3 branch with
> Zoltan Haindrich, he mentioned this letter:
> https://lists.apache.org/thread/by9ppc2z8oqdzpqotzv5bs34yrxrd84l
>
> I think Sungwoo Park and his team makes a huge effort to maintain this
> branch, and maybe it would be b
For 1, cherry-picking it to Hive 3 does not work. I tried to
backport HIVE-20911 to Hive 3, but it did not work because of so many
dependencies :-(
--- Sungwoo
On Thu, Aug 25, 2022 at 2:15 AM Bharathkrishna G M
wrote:
> Hi,
>
> I want to replicate the Hive metastore to create a separate
Hello Hive users,
MR3 1.5 has been released. Hive 3.1.3 (with more than 600 additional
patches backported) and Spark 3.2.2 are supported.
Hive/Spark on MR3 is a quick and ready solution for you if:
1. You want to migrate from Hadoop to Kubernetes, but continue to use Hive.
2. You want to run
In fact, Hive 3 has been much faster than Spark for a long time. For
complex queries, Hive 3 is much faster than Presto (or Trino) as well. The
reality is different from common beliefs on Hive, Spark, and Presto. If
interested, see the result of performance comparison using the TPC-DS
benchmark.
>
>
> [image: image.png]
>
> from your posting, the result is amazing. glad to know hive on mr3 has
> that nice performance.
>
Hive on MR3 is similar to Hive-LLAP in performance, so we can interpret the
above result as Hive being much faster than SparkSQL. For executing
concurrent queries, the
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
> On Sun, 8 Jan 2023 at 05:21, Sungwoo Park wrote:
>
>>
>&g
Hello,
A similar issue was discussed in the Tez mailing list a long time ago:
https://lists.apache.org/thread/0vjor12lpcncg43rn6vddw8yc1k62c81
Tez still does not support specifying node labels for AMs, but as explained
in the response, this is quite easy to implement if you can re-compile Tez.
Hello,
If you are interested in running Hive on Kubernetes (without requiring
Hadoop), we have updated the quick start guide on running Hive on MR3 on
Kubernetes.
The quick start guide shows step-by-step instructions for running
Metastore, HiveServer2, Ranger, MR3-UI, Grafana, with/without
Hi Hive users,
I am happy to announce the release of MR3 1.7. MR3 is an execution engine
for big data processing, and its main application Hive on MR3 is an
alternative to Hive-Tez and Hive-LLAP. I would like to summarize its main
features.
1. Hive on MR3 on Hadoop
Hive on MR3 is easy to install
Hello Hive users,
With the release of Hive on MR3 1.7, we published an article that compares
Trino, Spark, and Hive on MR3.
https://www.datamonad.com/post/2023-05-31-trino-spark-hive-performance-1.7/
Omitted in the article is the result of running Hive-LLAP included in HDP
3.1.4. In our
Hi Hive users,
Hive can persist runtime statistics by setting
hive.query.reexecution.stats.persist.scope to 'hiveserver' or 'metastore'
(instead of the default value 'query'). If you have an experience of using
this configuration key in production, could you share it here? (Like the
stability of
sues.apache.org/jira/browse/HIVE-26978
>
> On Wed, 24 May 2023 at 19:53, Sungwoo Park wrote:
>
>> Hi Hive users,
>>
>> Hive can persist runtime statistics by setting
>> hive.query.reexecution.stats.persist.scope to 'hiveserver' or 'metastore'
>> (ins
Hello Hive users,
I have published a new blog article 'Performance Tuning for Single-table
Queries'. It shows how to change configuration parameters of Hive and Tez
in order to make simple queries run faster than Spark. Although it
uses Hive on MR3, the technique equally applies to Hive on Tez
For Chinese users, MR3 1.8 is now shipped in HiDataPlus (along with
Celeborn).
https://mp.weixin.qq.com/s/65bgrnFpXtORlb4FjlPMWA
--- Sungwoo
On Sat, Dec 9, 2023 at 9:08 PM Sungwoo Park wrote:
> MR3 1.8 released
>
> On behalf of the MR3 team, I am pleased to announce the release o
MR3 1.8 released
On behalf of the MR3 team, I am pleased to announce the release of MR3 1.8.
MR3 is an execution engine similar in spirit to MapReduce and Tez which has
been under development since 2015. Its main application is Hive on MR3. You
can run Hive on MR3 on Hadoop, on Kubernetes, in
Hello,
I don't have an answer to your problem, but if your goal is to quickly test
Hive 3 using Docker, there is an alternative way which uses Hive on MR3.
https://mr3docs.datamonad.com/docs/quick/docker/
You can also run Hive on MR3 on Kubernetes.
Thanks,
--- Sungwoo
On Wed, Jan 10, 2024
Tez also
> works in standalone mode ?
>
> On Tue, Jan 9, 2024 at 11:08 PM Sungwoo Park wrote:
> >
> > Hello,
> >
> > I don't have an answer to your problem, but if your goal is to quickly
> test Hive 3 using Docker, there is an alternative way
Hello Hive users,
MR3 1.9 has been released. For changes, please see the release notes:
https://mr3docs.datamonad.com/docs/release/
https://mr3docs.datamonad.com/docs/release/#patches-backported-in-mr3-19
We evaluated the performance of Trino 435 and Hive on MR3 1.9 using the
TPC-DS benchmark.
we reverted HIVE-14187 and set
> connectionPoolingType=HikariCP (see No.7). Even with connectionPoolingType
> set to None, the environment where we reverted HIVE-14187 still performed
> reasonably well (see No.6).
>
> Please note our investigation is still ongoing and we haven't yet come to
>
metastore.stats.fetch.bitvector=true can also help generate more
efficient query plans.
--- Sungwoo
On Wed, Feb 28, 2024 at 1:40 PM Takanobu Asanuma
wrote:
> Hi Sungwoo Park,
>
> I'm sorry for the late reply to this old email.
> We are attempting to upgrade Hive MetaStore from Hive1 to Hive3, a
resolved in your fork of Hive 3.1.3?
> Thank you for sharing the issue with CachedStore and the JIRA tickets.
> I will also try out metastore.stats.fetch.bitvector=true.
>
> Regards,
> - Takanobu
>
> 2024年2月28日(水) 18:49 Sungwoo Park :
>
>> Hello Takanobu,
>>
>>
Hello Hive users,
We have released Hive on MR3 1.10. MR3 is an execution engine similar to
MapReduce and Tez, and it supports Hadoop, Kubernetes, and standalone mode.
Hive-MR3 uses MR3 for its execution backend in Hive 3.1.3. If you are
interested, please give it a try.
In MR3 1.10, we have
Congratulations and huge thanks to Apache Hive team and contributors for
releasing Hive 4. We have been watching the development of Hive 4 since the
release of Hive 3.1, and it's truly satisfying to witness the resolution of
all the critical issues at last after 5 years. Hive 4 comes with a lot of
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