To move data, Hive uses the LOAD statement. Move here means the original data is moved to the target table/partition and does not exist in the original place anymore. The LOCAL keyword in the LOAD statement specifies where the files are located on the client host. If the LOCAL keyword is not specified, the files are loaded from the full Uniform Resource Identifier (URI) specified after INPATH (most of the time, hdfs path) or the value from the fs.default.name property defined in hdfs-site.xml by default. The path after INPATH can be a relative path or an absolute path. The path either points to a file or a folder (referring to all files in the folder) to be loaded, but the subfolder is not allowed in the path specified. If the data is loaded into a partition table, the partition column must be specified. The OVERWRITE keyword is used to decide whether...
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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