impala/docs/topics/impala_insert.xml

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<!DOCTYPE concept PUBLIC "-//OASIS//DTD DITA Concept//EN" "concept.dtd">
<concept id="insert">

  <title>INSERT Statement</title>
  <titlealts audience="PDF"><navtitle>INSERT</navtitle></titlealts>
  <prolog>
    <metadata>
      <data name="Category" value="Impala"/>
      <data name="Category" value="SQL"/>
      <data name="Category" value="ETL"/>
      <data name="Category" value="Ingest"/>
      <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="S3"/>
      <data name="Category" value="Kudu"/>
      <!-- This is such an important statement, think if there are more applicable categories. -->
    </metadata>
  </prolog>

  <conbody>

    <p>
      <indexterm audience="hidden">INSERT statement</indexterm>
      Impala supports inserting into tables and partitions that you create with the Impala <codeph>CREATE
      TABLE</codeph> statement, or pre-defined tables and partitions created through Hive.
    </p>

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

<codeblock>[<varname>with_clause</varname>]
INSERT { INTO | OVERWRITE } [TABLE] <varname>table_name</varname>
  [(<varname>column_list</varname>)]
  [ PARTITION (<varname>partition_clause</varname>)]
{
    [<varname>hint_clause</varname>] <varname>select_statement</varname>
  | VALUES (<varname>value</varname> [, <varname>value</varname> ...]) [, (<varname>value</varname> [, <varname>value</varname> ...]) ...]
}

partition_clause ::= <varname>col_name</varname> [= <varname>constant</varname>] [, <varname>col_name</varname> [= <varname>constant</varname>] ...]

hint_clause ::= [SHUFFLE] | [NOSHUFFLE]    (Note: the square brackets are part of the syntax.)
</codeblock>

    <p>
      <b>Appending or replacing (INTO and OVERWRITE clauses):</b>
    </p>

    <p>
      The <codeph>INSERT INTO</codeph> syntax appends data to a table. The existing data files are left as-is, and
      the inserted data is put into one or more new data files.
    </p>

    <p>
      The <codeph>INSERT OVERWRITE</codeph> syntax replaces the data in a table.
<!-- What happens with INSERT OVERWRITE if the target is a single partition or multiple partitions? -->
<!-- If that gets too detailed, cover later under "Partitioning Considerations". -->
      Currently, the overwritten data files are deleted immediately; they do not go through the HDFS trash
      mechanism.
    </p>

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

    <p rev="2.3.0">
      The <codeph>INSERT</codeph> statement currently does not support writing data files
      containing complex types (<codeph>ARRAY</codeph>, <codeph>STRUCT</codeph>, and <codeph>MAP</codeph>).
      To prepare Parquet data for such tables, you generate the data files outside Impala and then
      use <codeph>LOAD DATA</codeph> or <codeph>CREATE EXTERNAL TABLE</codeph> to associate those
      data files with the table. Currently, such tables must use the Parquet file format.
      See <xref href="impala_complex_types.xml#complex_types"/> for details about working with complex types.
    </p>

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

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

    <p rev="kudu">
      Kudu tables require a unique primary key for each row. If an <codeph>INSERT</codeph>
      statement attempts to insert a row with the same values for the primary key columns
      as an existing row, that row is discarded and the insert operation continues.
      When rows are discarded due to duplicate primary keys, the statement finishes
      with a warning, not an error. (This is a change from early releases of Kudu
      where the default was to return in error in such cases, and the syntax
      <codeph>INSERT IGNORE</codeph> was required to make the statement succeed.
      The <codeph>IGNORE</codeph> clause is no longer part of the <codeph>INSERT</codeph>
      syntax.)
    </p>

    <p>
      For situations where you prefer to replace rows with duplicate primary key values,
      rather than discarding the new data, you can use the <codeph>UPSERT</codeph>
      statement instead of <codeph>INSERT</codeph>. <codeph>UPSERT</codeph> inserts
      rows that are entirely new, and for rows that match an existing primary key in the
      table, the non-primary-key columns are updated to reflect the values in the
      <q>upserted</q> data.
    </p>

    <p>
      If you really want to store new rows, not replace existing ones, but cannot do so
      because of the primary key uniqueness constraint, consider recreating the table
      with additional columns included in the primary key.
    </p>

    <p>
      See <xref href="impala_kudu.xml#impala_kudu"/> for more details about using Impala with Kudu.
    </p>

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

    <p>
      Impala currently supports:
    </p>

    <ul>
      <li>
        Copy data from another table using <codeph>SELECT</codeph> query. In Impala 1.2.1 and higher, you can
        combine <codeph>CREATE TABLE</codeph> and <codeph>INSERT</codeph> operations into a single step with the
        <codeph>CREATE TABLE AS SELECT</codeph> syntax, which bypasses the actual <codeph>INSERT</codeph> keyword.
      </li>

      <li>
        An optional <xref href="impala_with.xml#with"><codeph>WITH</codeph> clause</xref> before the
        <codeph>INSERT</codeph> keyword, to define a subquery referenced in the <codeph>SELECT</codeph> portion.
      </li>

      <li>
        Create one or more new rows using constant expressions through <codeph>VALUES</codeph> clause. (The
        <codeph>VALUES</codeph> clause was added in Impala 1.0.1.)
      </li>

      <li rev="1.1">
        <p>
          By default, the first column of each newly inserted row goes into the first column of the table, the
          second column into the second column, and so on.
        </p>
        <p>
          You can also specify the columns to be inserted, an arbitrarily ordered subset of the columns in the
          destination table, by specifying a column list immediately after the name of the destination table. This
          feature lets you adjust the inserted columns to match the layout of a <codeph>SELECT</codeph> statement,
          rather than the other way around. (This feature was added in Impala 1.1.)
        </p>
        <p>
          The number of columns mentioned in the column list (known as the <q>column permutation</q>) must match
          the number of columns in the <codeph>SELECT</codeph> list or the <codeph>VALUES</codeph> tuples. The
          order of columns in the column permutation can be different than in the underlying table, and the columns
          of each input row are reordered to match. If the number of columns in the column permutation is less than
          in the destination table, all unmentioned columns are set to <codeph>NULL</codeph>.
        </p>
      </li>

      <li>
        <p>
          For a partitioned table, the optional <codeph>PARTITION</codeph> clause identifies which partition or
          partitions the new values go into. If a partition key column is given a constant value such as
          <codeph>PARTITION (year=2012)</codeph> or <codeph>PARTITION (year=2012, month=2)</codeph>, all the
          inserted rows use those same values for those partition key columns and you omit any corresponding
          columns in the source table from the <codeph>SELECT</codeph> list. This form is known as <q>static
          partitioning</q>.
        </p>
        <p>
          If a partition key column is mentioned but not assigned a value, such as in <codeph>PARTITION (year,
          region)</codeph> (both columns unassigned) or <codeph>PARTITION(year, region='CA')</codeph>
          (<codeph>year</codeph> column unassigned), the unassigned columns are filled in with the final columns of
          the <codeph>SELECT</codeph> list. In this case, the number of columns in the <codeph>SELECT</codeph> list
          must equal the number of columns in the column permutation plus the number of partition key columns not
          assigned a constant value. This form is known as <q>dynamic partitioning</q>.
        </p>
        <p>
          See <xref href="impala_partitioning.xml#partition_static_dynamic"/> for examples and performance
          characteristics of static and dynamic partitioned inserts.
        </p>
      </li>

      <li rev="1.2.2">
        An optional hint clause immediately before the <codeph>SELECT</codeph> keyword, to fine-tune the behavior
        when doing an <codeph>INSERT ... SELECT</codeph> operation into partitioned Parquet tables. The hint
        keywords are <codeph>[SHUFFLE]</codeph> and <codeph>[NOSHUFFLE]</codeph>, including the square brackets.
        Inserting into partitioned Parquet tables can be a resource-intensive operation because it potentially
        involves many files being written to HDFS simultaneously, and separate
        <ph rev="parquet_block_size">large</ph> memory buffers being allocated to buffer the data for each
        partition. For usage details, see <xref href="impala_parquet.xml#parquet_etl"/>.
      </li>
    </ul>

    <note>
      <ul>
        <li>
          Insert commands that partition or add files result in changes to Hive metadata. Because Impala uses Hive
          metadata, such changes may necessitate a metadata refresh. For more information, see the
          <xref href="impala_refresh.xml#refresh">REFRESH</xref> function.
        </li>

        <li>
          Currently, Impala can only insert data into tables that use the text and Parquet formats. For other file
          formats, insert the data using Hive and use Impala to query it.
        </li>

        <li>
          As an alternative to the <codeph>INSERT</codeph> statement, if you have existing data files elsewhere in
          HDFS, the <codeph>LOAD DATA</codeph> statement can move those files into a table. This statement works
          with tables of any file format.
        </li>
      </ul>
    </note>

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

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

    <p>
      When you insert the results of an expression, particularly of a built-in function call, into a small numeric
      column such as <codeph>INT</codeph>, <codeph>SMALLINT</codeph>, <codeph>TINYINT</codeph>, or
      <codeph>FLOAT</codeph>, you might need to use a <codeph>CAST()</codeph> expression to coerce values into the
      appropriate type. Impala does not automatically convert from a larger type to a smaller one. For example, to
      insert cosine values into a <codeph>FLOAT</codeph> column, write <codeph>CAST(COS(angle) AS FLOAT)</codeph>
      in the <codeph>INSERT</codeph> statement to make the conversion explicit.
    </p>

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

    <p rev="DOCS-1523">
      Because Impala can read certain file formats that it cannot write,
      the <codeph>INSERT</codeph> statement does not work for all kinds of
      Impala tables. See <xref href="impala_file_formats.xml#file_formats"/>
      for details about what file formats are supported by the
      <codeph>INSERT</codeph> statement.
    </p>

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

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

    <note conref="../shared/impala_common.xml#common/compute_stats_next"/>

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

    <p>
      The following example sets up new tables with the same definition as the <codeph>TAB1</codeph> table from the
      <xref href="impala_tutorial.xml#tutorial">Tutorial</xref> section, using different file
      formats, and demonstrates inserting data into the tables created with the <codeph>STORED AS TEXTFILE</codeph>
      and <codeph>STORED AS PARQUET</codeph> clauses:
    </p>

<codeblock>CREATE DATABASE IF NOT EXISTS file_formats;
USE file_formats;

DROP TABLE IF EXISTS text_table;
CREATE TABLE text_table
( id INT, col_1 BOOLEAN, col_2 DOUBLE, col_3 TIMESTAMP )
STORED AS TEXTFILE;

DROP TABLE IF EXISTS parquet_table;
CREATE TABLE parquet_table
( id INT, col_1 BOOLEAN, col_2 DOUBLE, col_3 TIMESTAMP )
STORED AS PARQUET;</codeblock>

    <p>
      With the <codeph>INSERT INTO TABLE</codeph> syntax, each new set of inserted rows is appended to any existing
      data in the table. This is how you would record small amounts of data that arrive continuously, or ingest new
      batches of data alongside the existing data. For example, after running 2 <codeph>INSERT INTO TABLE</codeph>
      statements with 5 rows each, the table contains 10 rows total:
    </p>

<codeblock>[localhost:21000] &gt; insert into table text_table select * from default.tab1;
Inserted 5 rows in 0.41s

[localhost:21000] &gt; insert into table text_table select * from default.tab1;
Inserted 5 rows in 0.46s

[localhost:21000] &gt; select count(*) from text_table;
+----------+
| count(*) |
+----------+
| 10       |
+----------+
Returned 1 row(s) in 0.26s</codeblock>

    <p>
      With the <codeph>INSERT OVERWRITE TABLE</codeph> syntax, each new set of inserted rows replaces any existing
      data in the table. This is how you load data to query in a data warehousing scenario where you analyze just
      the data for a particular day, quarter, and so on, discarding the previous data each time. You might keep the
      entire set of data in one raw table, and transfer and transform certain rows into a more compact and
      efficient form to perform intensive analysis on that subset.
    </p>

    <p>
      For example, here we insert 5 rows into a table using the <codeph>INSERT INTO</codeph> clause, then replace
      the data by inserting 3 rows with the <codeph>INSERT OVERWRITE</codeph> clause. Afterward, the table only
      contains the 3 rows from the final <codeph>INSERT</codeph> statement.
    </p>

<codeblock>[localhost:21000] &gt; insert into table parquet_table select * from default.tab1;
Inserted 5 rows in 0.35s

[localhost:21000] &gt; insert overwrite table parquet_table select * from default.tab1 limit 3;
Inserted 3 rows in 0.43s
[localhost:21000] &gt; select count(*) from parquet_table;
+----------+
| count(*) |
+----------+
| 3        |
+----------+
Returned 1 row(s) in 0.43s</codeblock>

    <p>
      The <codeph><xref href="impala_insert.xml#values">VALUES</xref></codeph> clause lets you insert one or more
      rows by specifying constant values for all the columns. The number, types, and order of the expressions must
      match the table definition.
    </p>

    <note id="insert_values_warning">
      The <codeph>INSERT ... VALUES</codeph> technique is not suitable for loading large quantities of data into
      HDFS-based tables, because the insert operations cannot be parallelized, and each one produces a separate
      data file. Use it for setting up small dimension tables or tiny amounts of data for experimenting with SQL
      syntax, or with HBase tables. Do not use it for large ETL jobs or benchmark tests for load operations. Do not
      run scripts with thousands of <codeph>INSERT ... VALUES</codeph> statements that insert a single row each
      time. If you do run <codeph>INSERT ... VALUES</codeph> operations to load data into a staging table as one
      stage in an ETL pipeline, include multiple row values if possible within each <codeph>VALUES</codeph> clause,
      and use a separate database to make cleanup easier if the operation does produce many tiny files.
    </note>

    <p>
      The following example shows how to insert one row or multiple rows, with expressions of different types,
      using literal values, expressions, and function return values:
    </p>

<codeblock>create table val_test_1 (c1 int, c2 float, c3 string, c4 boolean, c5 timestamp);
insert into val_test_1 values (100, 99.9/10, 'abc', true, now());
create table val_test_2 (id int, token string);
insert overwrite val_test_2 values (1, 'a'), (2, 'b'), (-1,'xyzzy');</codeblock>

    <p>
      These examples show the type of <q>not implemented</q> error that you see when attempting to insert data into
      a table with a file format that Impala currently does not write to:
    </p>

<codeblock>DROP TABLE IF EXISTS sequence_table;
CREATE TABLE sequence_table
( id INT, col_1 BOOLEAN, col_2 DOUBLE, col_3 TIMESTAMP )
STORED AS SEQUENCEFILE;

DROP TABLE IF EXISTS rc_table;
CREATE TABLE rc_table
( id INT, col_1 BOOLEAN, col_2 DOUBLE, col_3 TIMESTAMP )
STORED AS RCFILE;

[localhost:21000] &gt; insert into table rc_table select * from default.tab1;
Remote error
Backend 0:RC_FILE not implemented.

[localhost:21000] &gt; insert into table sequence_table select * from default.tab1;
Remote error
Backend 0:SEQUENCE_FILE not implemented. </codeblock>

    <p>
      Inserting data into partitioned tables requires slightly different syntax that divides the partitioning
      columns from the others:
    </p>

<codeblock>create table t1 (i int) <b>partitioned by (x int, y string)</b>;
-- Select an INT column from another table.
-- All inserted rows will have the same x and y values, as specified in the INSERT statement.
-- This technique of specifying all the partition key values is known as static partitioning.
insert into t1 <b>partition(x=10, y='a')</b> select c1 from some_other_table;
-- Select two INT columns from another table.
-- All inserted rows will have the same y value, as specified in the INSERT statement.
-- Values from c2 go into t1.x.
-- Any partitioning columns whose value is not specified are filled in
-- from the columns specified last in the SELECT list.
-- This technique of omitting some partition key values is known as dynamic partitioning.
insert into t1 <b>partition(x, y='b')</b> select c1, c2 from some_other_table;
-- Select an INT and a STRING column from another table.
-- All inserted rows will have the same x value, as specified in the INSERT statement.
-- Values from c3 go into t1.y.
insert into t1 <b>partition(x=20, y)</b> select c1, c3  from some_other_table;</codeblock>

    <p rev="1.1">
      The following examples show how you can copy the data in all the columns from one table to another, copy the
      data from only some columns, or specify the columns in the select list in a different order than they
      actually appear in the table:
    </p>

<codeblock>-- Start with 2 identical tables.
create table t1 (c1 int, c2 int);
create table t2 like t1;

-- If there is no () part after the destination table name,
-- all columns must be specified, either as * or by name.
insert into t2 select * from t1;
insert into t2 select c1, c2 from t1;

-- With the () notation following the destination table name,
-- you can omit columns (all values for that column are NULL
-- in the destination table), and/or reorder the values
-- selected from the source table. This is the "column permutation" feature.
insert into t2 (c1) select c1 from t1;
insert into t2 (c2, c1) select c1, c2 from t1;

-- The column names can be entirely different in the source and destination tables.
-- You can copy any columns, not just the corresponding ones, from the source table.
-- But the number and type of selected columns must match the columns mentioned in the () part.
alter table t2 replace columns (x int, y int);
insert into t2 (y) select c1 from t1;

-- For partitioned tables, all the partitioning columns must be mentioned in the () column list
-- or a PARTITION clause; these columns cannot be defaulted to NULL.
create table pt1 (x int, y int) partitioned by (z int);
-- The values from c1 are copied into the column x in the new table,
-- all in the same partition based on a constant value for z.
-- The values of y in the new table are all NULL.
insert into pt1 (x) partition (z=5) select c1 from t1;
-- Again we omit the values for column y so they are all NULL.
-- The inserted x values can go into different partitions, based on
-- the different values inserted into the partitioning column z.
insert into pt1 (x,z) select x, z from t2;
</codeblock>

    <p>
      <codeph>SELECT *</codeph> for a partitioned table requires that all partition key columns in the source table
      be declared as the last columns in the <codeph>CREATE TABLE</codeph> statement. You still include a
      <codeph>PARTITION BY</codeph> clause listing all the partition key columns. These partition columns are
      automatically mapped to the last columns from the <codeph>SELECT *</codeph> list.
    </p>

<codeblock>create table source (x int, y int, year int, month int, day int);
create table destination (x int, y int) partitioned by (year int, month int, day int);
...load some data into the unpartitioned source table...
-- Insert a single partition of data.
-- The SELECT * means you cannot specify partition (year=2014, month, day).
insert overwrite destination partition (year, month, day) select * from source where year=2014;
-- Insert the data for all year/month/day combinations.
insert overwrite destination partition (year, month, day) select * from source;

-- If one of the partition columns is omitted from the source table,
-- then you can specify a specific value for that column in the PARTITION clause.
-- Here the source table holds only data from 2014, and so does not include a year column.
create table source_2014 (x int, y int, month, day);
...load some data into the unpartitioned source_2014 table...
insert overwrite destination partition (year=2014, month, day) select * from source_2014;
</codeblock>

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

    <p>
      <b>Concurrency considerations:</b> Each <codeph>INSERT</codeph> operation creates new data files with unique
      names, so you can run multiple <codeph>INSERT INTO</codeph> statements simultaneously without filename
      conflicts.
<!--
If data is inserted into a table by a statement issued to a different
<cmdname>impalad</cmdname> node,
issue a <codeph>REFRESH <varname>table_name</varname></codeph>
statement to make the node you are connected to aware of this new data.
-->
      While data is being inserted into an Impala table, the data is staged temporarily in a subdirectory inside
      the data directory; during this period, you cannot issue queries against that table in Hive. If an
      <codeph>INSERT</codeph> operation fails, the temporary data file and the subdirectory could be left behind in
      the data directory. If so, remove the relevant subdirectory and any data files it contains manually, by
      issuing an <codeph>hdfs dfs -rm -r</codeph> command, specifying the full path of the work subdirectory, whose
      name ends in <codeph>_dir</codeph>.
    </p>
  </conbody>

  <concept id="values">

    <title>VALUES Clause</title>

    <conbody>

      <p>
        The <codeph>VALUES</codeph> clause is a general-purpose way to specify the columns of one or more rows,
        typically within an <codeph><xref href="impala_insert.xml#insert">INSERT</xref></codeph> statement.
      </p>

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

      <p>
        The following examples illustrate:
      </p>

      <ul>
        <li>
          How to insert a single row using a <codeph>VALUES</codeph> clause.
        </li>

        <li>
          How to insert multiple rows using a <codeph>VALUES</codeph> clause.
        </li>

        <li>
          How the row or rows from a <codeph>VALUES</codeph> clause can be appended to a table through
          <codeph>INSERT INTO</codeph>, or replace the contents of the table through <codeph>INSERT
          OVERWRITE</codeph>.
        </li>

        <li>
          How the entries in a <codeph>VALUES</codeph> clause can be literals, function results, or any other kind
          of expression. See <xref href="impala_literals.xml#literals"/> for the notation to use for literal
          values, especially <xref href="impala_literals.xml#string_literals"/> for quoting and escaping
          conventions for strings. See <xref href="impala_operators.xml#operators"/> and
          <xref href="impala_functions.xml#builtins"/> for other things you can include in expressions with the
          <codeph>VALUES</codeph> clause.
        </li>
      </ul>

<codeblock>[localhost:21000] &gt; describe val_example;
Query: describe val_example
Query finished, fetching results ...
+-------+---------+---------+
| name  | type    | comment |
+-------+---------+---------+
| id    | int     |         |
| col_1 | boolean |         |
| col_2 | double  |         |
+-------+---------+---------+

[localhost:21000] &gt; insert into val_example values (1,true,100.0);
Inserted 1 rows in 0.30s
[localhost:21000] &gt; select * from val_example;
+----+-------+-------+
| id | col_1 | col_2 |
+----+-------+-------+
| 1  | true  | 100   |
+----+-------+-------+

[localhost:21000] &gt; insert overwrite val_example values (10,false,pow(2,5)), (50,true,10/3);
Inserted 2 rows in 0.16s
[localhost:21000] &gt; select * from val_example;
+----+-------+-------------------+
| id | col_1 | col_2             |
+----+-------+-------------------+
| 10 | false | 32                |
| 50 | true  | 3.333333333333333 |
+----+-------+-------------------+</codeblock>

      <p>
        When used in an <codeph>INSERT</codeph> statement, the Impala <codeph>VALUES</codeph> clause can specify
        some or all of the columns in the destination table, and the columns can be specified in a different order
        than they actually appear in the table. To specify a different set or order of columns than in the table,
        use the syntax:
      </p>

<codeblock>INSERT INTO <varname>destination</varname>
  (<varname>col_x</varname>, <varname>col_y</varname>, <varname>col_z</varname>)
  VALUES
  (<varname>val_x</varname>, <varname>val_y</varname>, <varname>val_z</varname>);
</codeblock>

      <p>
        Any columns in the table that are not listed in the <codeph>INSERT</codeph> statement are set to
        <codeph>NULL</codeph>.
      </p>

<!--
      <p>
        does not support specifying a subset of the
        columns in the table or specifying the columns in a different order. Use a
        <codeph>VALUES</codeph> clause with all the column values in the same order as
        the table definition, using <codeph>NULL</codeph> values for any columns you
        want to omit from the <codeph>INSERT</codeph> operation.
      </p>
-->

      <p>
        To use a <codeph>VALUES</codeph> clause like a table in other statements, wrap it in parentheses and use
        <codeph>AS</codeph> clauses to specify aliases for the entire object and any columns you need to refer to:
      </p>

<codeblock>[localhost:21000] &gt; select * from (values(4,5,6),(7,8,9)) as t;
+---+---+---+
| 4 | 5 | 6 |
+---+---+---+
| 4 | 5 | 6 |
| 7 | 8 | 9 |
+---+---+---+
[localhost:21000] &gt; select * from (values(1 as c1, true as c2, 'abc' as c3),(100,false,'xyz')) as t;
+-----+-------+-----+
| c1  | c2    | c3  |
+-----+-------+-----+
| 1   | true  | abc |
| 100 | false | xyz |
+-----+-------+-----+</codeblock>

      <p>
        For example, you might use a tiny table constructed like this from constant literals or function return
        values as part of a longer statement involving joins or <codeph>UNION ALL</codeph>.
      </p>

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

      <p>
        Impala physically writes all inserted files under the ownership of its default user, typically
        <codeph>impala</codeph>. Therefore, this user must have HDFS write permission in the corresponding table
        directory.
      </p>

      <p>
        The permission requirement is independent of the authorization performed by the Sentry framework. (If the
        connected user is not authorized to insert into a table, Sentry blocks that operation immediately,
        regardless of the privileges available to the <codeph>impala</codeph> user.) Files created by Impala are
        not owned by and do not inherit permissions from the connected user.
      </p>

      <p>
        The number of data files produced by an <codeph>INSERT</codeph> statement depends on the size of the
        cluster, the number of data blocks that are processed, the partition key columns in a partitioned table,
        and the mechanism Impala uses for dividing the work in parallel. Do not assume that an
        <codeph>INSERT</codeph> statement will produce some particular number of output files. In case of
        performance issues with data written by Impala, check that the output files do not suffer from issues such
        as many tiny files or many tiny partitions. (In the Hadoop context, even files or partitions of a few tens
        of megabytes are considered <q>tiny</q>.)
      </p>

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

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

      <p>
        You can use the <codeph>INSERT</codeph> statement with HBase tables as follows:
      </p>

      <ul>
        <li>
          <p>
            You can insert a single row or a small set of rows into an HBase table with the <codeph>INSERT ...
            VALUES</codeph> syntax. This is a good use case for HBase tables with Impala, because HBase tables are
            not subject to the same kind of fragmentation from many small insert operations as HDFS tables are.
          </p>
        </li>

        <li>
          <p>
            You can insert any number of rows at once into an HBase table using the <codeph>INSERT ...
            SELECT</codeph> syntax.
          </p>
        </li>

        <li>
          <p>
            If more than one inserted row has the same value for the HBase key column, only the last inserted row
            with that value is visible to Impala queries. You can take advantage of this fact with <codeph>INSERT
            ... VALUES</codeph> statements to effectively update rows one at a time, by inserting new rows with the
            same key values as existing rows. Be aware that after an <codeph>INSERT ... SELECT</codeph> operation
            copying from an HDFS table, the HBase table might contain fewer rows than were inserted, if the key
            column in the source table contained duplicate values.
          </p>
        </li>

        <li>
          <p>
            You cannot <codeph>INSERT OVERWRITE</codeph> into an HBase table. New rows are always appended.
          </p>
        </li>

        <li>
          <p>
            When you create an Impala or Hive table that maps to an HBase table, the column order you specify with
            the <codeph>INSERT</codeph> statement might be different than the order you declare with the
            <codeph>CREATE TABLE</codeph> statement. Behind the scenes, HBase arranges the columns based on how
            they are divided into column families. This might cause a mismatch during insert operations, especially
            if you use the syntax <codeph>INSERT INTO <varname>hbase_table</varname> SELECT * FROM
            <varname>hdfs_table</varname></codeph>. Before inserting data, verify the column order by issuing a
            <codeph>DESCRIBE</codeph> statement for the table, and adjust the order of the select list in the
            <codeph>INSERT</codeph> statement.
          </p>
        </li>
      </ul>

      <p>
        See <xref href="impala_hbase.xml#impala_hbase"/> for more details about using Impala with HBase.
      </p>

      <p conref="../shared/impala_common.xml#common/s3_blurb"/>
      <p conref="../shared/impala_common.xml#common/s3_dml"/>
      <p conref="../shared/impala_common.xml#common/s3_dml_performance"/>
      <p>See <xref href="../topics/impala_s3.xml#s3"/> for details about reading and writing S3 data with Impala.</p>

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

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

      <p conref="../shared/impala_common.xml#common/permissions_blurb"/>
      <p rev="">
        The user ID that the <cmdname>impalad</cmdname> daemon runs under,
        typically the <codeph>impala</codeph> user, must have read
        permission for the files in the source directory of an <codeph>INSERT ... SELECT</codeph>
        operation, and write permission for all affected directories in the destination table.
        (An <codeph>INSERT</codeph> operation could write files to multiple different HDFS directories
        if the destination table is partitioned.)
        This user must also have write permission to create a temporary work directory
        in the top-level HDFS directory of the destination table.
        An <codeph>INSERT OVERWRITE</codeph> operation does not require write permission on
        the original data files in the table, only on the table directories themselves.
      </p>

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

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

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

      <p rev="1.3.1" conref="../shared/impala_common.xml#common/insert_inherit_permissions"/>
    </conbody>
  </concept>

<!-- Values clause -->
</concept>
<!-- INSERT statement -->