docs/topics/impala_dml.xml

<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE concept PUBLIC "-//OASIS//DTD DITA Concept//EN" "concept.dtd">
<concept id="dml">

  <title>DML Statements</title>
  <prolog>
    <metadata>
      <data name="Category" value="Impala"/>
      <data name="Category" value="SQL"/>
      <data name="Category" value="DML"/>
      <data name="Category" value="Data Analysts"/>
      <data name="Category" value="Developers"/>
      <data name="Category" value="Tables"/>
      <data name="Category" value="ETL"/>
      <data name="Category" value="Ingest"/>
    </metadata>
  </prolog>

  <conbody>

    <p>
      DML refers to <q>Data Manipulation Language</q>, a subset of SQL statements that modify the data stored in
      tables. Because Impala focuses on query performance and leverages the append-only nature of HDFS storage,
      currently Impala only supports a small set of DML statements:
    </p>

    <ul>
      <li>
        <xref keyref="delete"/>. Works for Kudu tables only.
      </li>

      <li>
        <xref keyref="insert"/>.
      </li>

      <li>
        <xref keyref="load_data"/>. Does not apply for HBase or Kudu tables.
      </li>

      <li>
        <xref keyref="update"/>. Works for Kudu tables only.
      </li>

      <li>
        <xref keyref="upsert"/>. Works for Kudu tables only.
      </li>
    </ul>

    <p>
      <codeph>INSERT</codeph> in Impala is primarily optimized for inserting large volumes of data in a single
      statement, to make effective use of the multi-megabyte HDFS blocks. This is the way in Impala to create new
      data files. If you intend to insert one or a few rows at a time, such as using the <codeph>INSERT ...
      VALUES</codeph> syntax, that technique is much more efficient for Impala tables stored in HBase. See
      <xref href="impala_hbase.xml#impala_hbase"/> for details.
    </p>

    <p>
      <codeph>LOAD DATA</codeph> moves existing data files into the directory for an Impala table, making them
      immediately available for Impala queries. This is one way in Impala to work with data files produced by other
      Hadoop components. (<codeph>CREATE EXTERNAL TABLE</codeph> is the other alternative; with external tables,
      you can query existing data files, while the files remain in their original location.)
    </p>

    <p>
      In <keyword keyref="impala28_full"/> and higher, Impala does support the <codeph>UPDATE</codeph>, <codeph>DELETE</codeph>,
      and <codeph>UPSERT</codeph> statements for Kudu tables.
      For HDFS or S3 tables, to simulate the effects of an <codeph>UPDATE</codeph> or <codeph>DELETE</codeph> statement
      in other database systems, typically you use <codeph>INSERT</codeph> or <codeph>CREATE TABLE AS SELECT</codeph> to copy data
      from one table to another, filtering out or changing the appropriate rows during the copy operation.
    </p>

    <p>
      You can also achieve a result similar to <codeph>UPDATE</codeph> by using Impala tables stored in HBase.
      When you insert a row into an HBase table, and the table
      already contains a row with the same value for the key column, the older row is hidden, effectively the same
      as a single-row <codeph>UPDATE</codeph>.
    </p>

    <p rev="2.6.0">
      Impala can perform DML operations for tables or partitions stored in the Amazon S3 filesystem
      with <keyword keyref="impala26_full"/> and higher. See <xref href="impala_s3.xml#s3"/> for details.
    </p>

    <p conref="../shared/impala_common.xml#common/related_info"/>

    <p>
      The other major classifications of SQL statements are data definition language (see
      <xref href="impala_ddl.xml#ddl"/>) and queries (see <xref href="impala_select.xml#select"/>).
    </p>
  </conbody>
</concept>