A data type used in CREATE TABLE and ALTER TABLE statements.

In the column definition of a CREATE TABLE and ALTER TABLE statements:

Length:

If you need to manipulate string values with precise or maximum lengths, in Impala 2.0 and higher you can declare columns as VARCHAR(max_length) or CHAR(length), but for best performance use STRING where practical.

Take the following considerations for STRING lengths:

• The hard limit on the size of a STRING and the total size of a row is 2 GB.

  If a query tries to process or create a string larger than this limit, it will return an error to the user.

• The limit is 1 GB on STRING when writing to Parquet files.
• Queries operating on strings with 32 KB or less will work reliably and will not hit significant performance or memory problems (unless you have very complex queries, very many columns, etc.)
• Performance and memory consumption may degrade with strings larger than 32 KB.
• The row size, i.e. the total size of all string and other columns, is subject to lower limits at various points in query execution that support spill-to-disk. A few examples for lower row size limits are:
  • Rows coming from the right side of any hash join
  • Rows coming from either side of a hash join that spills to disk
  • Rows being sorted by the SORT operator without a limit
  • Rows in a grouping aggregation

  In and lower, the default limit of the row size in the above cases is 8 MB.

  In and higher, the max row size is configurable on a per-query basis with the MAX_ROW_SIZE query option. Rows up to MAX_ROW_SIZE (which defaults to 512 KB) can always be processed in the above cases. Rows larger than MAX_ROW_SIZE are processed on a best-effort basis. See MAX_ROW_SIZE for more details.

Character sets:

For full support in all Impala subsystems, restrict string values to the ASCII character set. Although some UTF-8 character data can be stored in Impala and retrieved through queries, UTF-8 strings containing non-ASCII characters are not guaranteed to work properly in combination with many SQL aspects, including but not limited to:

• String manipulation functions.
• Comparison operators.
• The ORDER BY clause.
• Values in partition key columns.

For any national language aspects such as collation order or interpreting extended ASCII variants such as ISO-8859-1 or ISO-8859-2 encodings, Impala does not include such metadata with the table definition. If you need to sort, manipulate, or display data depending on those national language characteristics of string data, use logic on the application side.

Conversions:

• Impala does not automatically convert STRING to any numeric type. Impala does automatically convert STRING to TIMESTAMP if the value matches one of the accepted TIMESTAMP formats; see for details.

• You can use CAST() to convert STRING values to TINYINT, SMALLINT, INT, BIGINT, FLOAT, DOUBLE, or TIMESTAMP.

• You cannot directly cast a STRING value to BOOLEAN. You can use a CASE expression to evaluate string values such as 'T', 'true', and so on and return Boolean true and false values as appropriate.

• You can cast a BOOLEAN value to STRING, returning '1' for true values and '0' for false values.

Although it might be convenient to use STRING columns for partition keys, even when those columns contain numbers, for performance and scalability it is much better to use numeric columns as partition keys whenever practical. Although the underlying HDFS directory name might be the same in either case, the in-memory storage for the partition key columns is more compact, and computations are faster, if partition key columns such as YEAR, MONTH, DAY and so on are declared as INT, SMALLINT, and so on.

Avro considerations:

The following examples demonstrate double-quoted and single-quoted string literals, and required escaping for quotation marks within string literals:

The following examples demonstrate calls to string manipulation functions to concatenate strings, convert numbers to strings, or pull out substrings:

The following examples show how to perform operations on STRING columns within a table:

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