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/> *Disclaimer:* Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise 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 Thu, 10 Jun 2021 at 22:11, Chao Sun <sunc...@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 > >
