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<!DOCTYPE concept PUBLIC "-//OASIS//DTD DITA Concept//EN" "concept.dtd">
<concept id="functions">
<title>Overview of Impala Functions</title>
<titlealts audience="PDF"><navtitle>Functions</navtitle></titlealts>
<data name="Category" value="Impala"/>
<data name="Category" value="Impala Functions"/>
<data name="Category" value="SQL"/>
<data name="Category" value="Data Analysts"/>
<data name="Category" value="Developers"/>
Functions let you apply arithmetic, string, or other computations and transformations to Impala data. You
typically use them in <codeph>SELECT</codeph> lists and <codeph>WHERE</codeph> clauses to filter and format
query results so that the result set is exactly what you want, with no further processing needed on the
application side.
Scalar functions return a single result for each input row. See <xref href="impala_functions.xml#builtins"/>.
<codeblock>[localhost:21000] > select name, population from country where continent = 'North America' order by population desc limit 4;
[localhost:21000] > select upper(name), population from country where continent = 'North America' order by population desc limit 4;
| upper(name) | population |
| USA | 320000000 |
| MEXICO | 122000000 |
| CANADA | 25000000 |
| GUATEMALA | 16000000 |
Aggregate functions combine the results from multiple rows:
either a single result for the entire table, or a separate result for each group of rows.
Aggregate functions are frequently used in combination with <codeph>GROUP BY</codeph>
and <codeph>HAVING</codeph> clauses in the <codeph>SELECT</codeph> statement.
See <xref href="impala_aggregate_functions.xml#aggregate_functions"/>.
<codeblock>[localhost:21000] > select continent, <b>sum(population)</b> as howmany from country <b>group by continent</b> order by howmany desc;
| continent | howmany |
| Asia | 4298723000 |
| Africa | 1110635000 |
| Europe | 742452000 |
| North America | 565265000 |
| South America | 406740000 |
| Oceania | 38304000 |
User-defined functions (UDFs) let you code your own logic. They can be either scalar or aggregate functions.
UDFs let you implement important business or scientific logic using high-performance code for Impala to automatically parallelize.
You can also use UDFs to implement convenience functions to simplify reporting or porting SQL from other database systems.
See <xref href="impala_udf.xml#udfs"/>.
<codeblock>[localhost:21000] > select <b>rot13('Hello world!')</b> as 'Weak obfuscation';
| weak obfuscation |
| Uryyb jbeyq! |
[localhost:21000] > select <b>likelihood_of_new_subatomic_particle(sensor1, sensor2, sensor3)</b> as probability
> from experimental_results group by experiment;
Each function is associated with a specific database. For example, if you issue a <codeph>USE somedb</codeph>
statement followed by <codeph>CREATE FUNCTION somefunc</codeph>, the new function is created in the
<codeph>somedb</codeph> database, and you could refer to it through the fully qualified name
<codeph>somedb.somefunc</codeph>. You could then issue another <codeph>USE</codeph> statement
and create a function with the same name in a different database.
Impala built-in functions are associated with a special database named <codeph>_impala_builtins</codeph>,
which lets you refer to them from any database without qualifying the name.
<codeblock>[localhost:21000] > show databases;
| name |
| <b>_impala_builtins</b> |
| analytic_functions |
| avro_testing |
| data_file_size |
[localhost:21000] > show functions in _impala_builtins like '*subs*';
| return type | signature |
| STRING | substring(STRING, BIGINT) |
<b>Related statements:</b> <xref href="impala_create_function.xml#create_function"/>,
<xref href="impala_drop_function.xml#drop_function"/>