Hive's Data Definition Language (DDL) is a subset of HQL statements that describe the Hive data structure by creating, deleting, or altering schema objects such as databases, tables, views, partitions, and buckets. Most DDL statements start with the CREATE, DROP, or ALTER keywords. The syntax of HQL DDL is very similar to SQL DDL. In the next section, we'll focus on the details of HQL DDL.
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You're reading from Apache Hive Essentials. - Second Edition
Dayong Du has all his career dedicated to enterprise data and analytics for more than 10 years, especially on enterprise use case with open source big data technology, such as Hadoop, Hive, HBase, Spark, etc. Dayong is a big data practitioner as well as author and coach. He has published the 1st and 2nd edition of Apache Hive Essential and coached lots of people who are interested to learn and use big data technology. In addition, he is a seasonal blogger, contributor, and advisor for big data start-ups, co-founder of Toronto big data professional association.
Read more about Dayong Du
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Dayong Du has all his career dedicated to enterprise data and analytics for more than 10 years, especially on enterprise use case with open source big data technology, such as Hadoop, Hive, HBase, Spark, etc. Dayong is a big data practitioner as well as author and coach. He has published the 1st and 2nd edition of Apache Hive Essential and coached lots of people who are interested to learn and use big data technology. In addition, he is a seasonal blogger, contributor, and advisor for big data start-ups, co-founder of Toronto big data professional association.
Read more about Dayong Du