[ANNOUNCE] Apache Hive 2.3.9 Released

[Chao Sun <su...@apache.org>]

The Apache Hive team is proud to announce the release of Apache Hive
version 2.3.9.

The Apache Hive (TM) data warehouse software facilitates querying and
managing large datasets residing in distributed storage. Built on top of
Apache Hadoop (TM), it provides, among others:

* Tools to enable easy data extract/transform/load (ETL)
* A mechanism to impose structure on a variety of data formats
* Access to files stored either directly in Apache HDFS (TM) or in other
data storage systems such as Apache HBase (TM)
* Query execution via Apache Hadoop MapReduce, Apache Tez and Apache Spark
frameworks.

For Hive release details and downloads, please visit:
https://hive.apache.org/downloads.html
Hive 2.3.9 Release Notes are available here:
https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12350009&styleName=Html&projectId=12310843

We would like to thank the many contributors who made this release possible.

Regards,
The Apache Hive Team

Re: [ANNOUNCE] Apache Hive 2.3.9 Released

[Mich Talebzadeh <mi...@gmail.com>]

Dear Announcer and the vibrant Hive community

I must congratulate Hive development and the user community for investing,
contributing and keeping a strong Apache Hive Data Warehouse on HDFS.

In July 2016, I made a presentation in conjunction with Hortonworks on the
topic of Query Engines for Hive: MR, Spark, Tez with LLAP – Considerations!
<https://www.slideshare.net/MichTalebzadeh1/query-engines-for-hive-mr-spark-tez-with-llap-considerations>


That was on Hive 1.3.1. I am very glad to see Apache Hive
<https://en.wikipedia.org/wiki/Apache_Hive>going strong and indeed being so
popular after nearly 11 years from its first release. No doubt Hive is a
flagship product and it is an essential part of any storage and ETL work
with its versatile architecture in Big Data and Cloud world. Additionally,
it is probably the first artifact for many SQL savvy people to make
themselves familiar with Big Data.

Worth noting that Apache Hive has been a pioneer in supporting additional
Big Data tools like Apache Spark <https://spark.apache.org/> whose Spark
SQL <https://spark.apache.org/docs/latest/sql-programming-guide.html>is
largely built on top of Hive SQL. Google BigQuery Data Warehouse
<https://cloud.google.com/bigquery> is built largely from concepts
inherited from our humble Apache Hive. I often refer to BigQuery as Hive on
steroids. Even Databricks Data Lake
<https://databricks.com/glossary/data-lake>has a lot of concepts borrowed
from Apache Hive.

Looking forward to seeing many happy years with Apache Hive.





   view my Linkedin profile
<https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>



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On Thu, 10 Jun 2021 at 22:11, Chao Sun <su...@apache.org> wrote:

> The Apache Hive team is proud to announce the release of Apache Hive
> version 2.3.9.
>
> The Apache Hive (TM) data warehouse software facilitates querying and
> managing large datasets residing in distributed storage. Built on top of
> Apache Hadoop (TM), it provides, among others:
>
> * Tools to enable easy data extract/transform/load (ETL)
> * A mechanism to impose structure on a variety of data formats
> * Access to files stored either directly in Apache HDFS (TM) or in other
> data storage systems such as Apache HBase (TM)
> * Query execution via Apache Hadoop MapReduce, Apache Tez and Apache Spark
> frameworks.
>
> For Hive release details and downloads, please visit:
> https://hive.apache.org/downloads.html
> Hive 2.3.9 Release Notes are available here:
> https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12350009&styleName=Html&projectId=12310843
>
> We would like to thank the many contributors who made this release
> possible.
>
> Regards,
> The Apache Hive Team
>
>