Functions
CQL supports 2 main categories of functions:
scalar functions that take a number of values and produce an output
aggregate functions that aggregate multiple rows resulting from a
SELECT
statement
In both cases, CQL provides a number of native “hard-coded” functions as well as the ability to create new user-defined functions.
Note By default, the use of user-defined functions is disabled by default for security concerns (even when enabled, the execution of user-defined functions is sandboxed and a “rogue” function should not be allowed to do evil, but no sandbox is perfect so using user-defined functions is opt-in). See the |
A function is identifier by its name:
function_name ::= [ keyspace_name'.' ] name
Scalar functions
Native functions
Cast
The cast
function can be used to converts one native datatype to another.
The following table describes the conversions supported by the cast
function. Cassandra will silently ignore any cast converting a datatype into its own datatype.
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The conversions rely strictly on Java’s semantics. For example, the double value 1 will be converted to the text value ‘1.0’. For instance:
SELECT avg(cast(count as double)) FROM myTable
Token
The token
function computes the token for a given partition key. The exact signature of the token function depends on the table concerned and the partitioner used by the cluster.
The type of the arguments of the token
depend on the partition key column type. The returned type depends on the defined partitioner:
Partitioner | Returned type |
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Murmur3Partitioner |
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RandomPartitioner |
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ByteOrderedPartitioner |
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For example, consider the following table:
CREATE TABLE users (
userid text PRIMARY KEY,
username text,
);
The table uses the default Murmur3Partitioner. The token
function uses the single argument text
, because the partition key is userid
of text type. The returned type will be bigint
.
Uuid
The uuid
function takes no parameters and generates a random type 4 uuid suitable for use in INSERT
or UPDATE
statements.
Timeuuid functions
now
The now
function takes no arguments and generates, on the coordinator node, a new unique timeuuid at the time the function is invoked. Note that this method is useful for insertion but is largely non-sensical in WHERE
clauses.
For example, a query of the form:
SELECT * FROM myTable WHERE t = now();
will not return a result, by design, since the value returned by now()
is guaranteed to be unique.
currentTimeUUID
is an alias of now
.
minTimeuuid and maxTimeuuid
The minTimeuuid
function takes a timestamp
value t
, either a timestamp or a date string. It returns a fake timeuuid
corresponding to the smallest possible timeuuid
for timestamp t
. The maxTimeuuid
works similarly, but returns the largest possible timeuuid
.
For example:
SELECT * FROM myTable
WHERE t > maxTimeuuid('2013-01-01 00:05+0000')
AND t < minTimeuuid('2013-02-02 10:00+0000');
will select all rows where the timeuuid
column t
is later than '2013-01-01 00:05+0000'
and earlier than '2013-02-02 10:00+0000'
. The clause t >= maxTimeuuid('2013-01-01 00:05+0000')
would still not select a timeuuid
generated exactly at ‘2013-01-01 00:05+0000’, and is essentially equivalent to t > maxTimeuuid('2013-01-01 00:05+0000')
.
Note The values generated by |
Datetime functions
Retrieving the current date/time
The following functions can be used to retrieve the date/time at the time where the function is invoked:
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For example the last two days of data can be retrieved using:
SELECT * FROM myTable WHERE date >= currentDate() - 2d;
Time conversion functions
A number of functions are provided to convert a timeuuid
, a timestamp
or a date
into another native
type.
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Blob conversion functions
A number of functions are provided to convert the native types into binary data, or a blob
. For every type supported by CQL, the function typeAsBlob
takes a argument of type type
and returns it as a blob
. Conversely, the function blobAsType
takes a 64-bit blob
argument and converts it to a bigint
value. For example, bigintAsBlob(3)
returns 0x0000000000000003
and blobAsBigint(0x0000000000000003)
returns 3
.
User-defined functions
User-defined functions (UDFs) execute user-provided code in Cassandra. By default, Cassandra supports defining functions in Java and JavaScript. Support for other JSR 223 compliant scripting languages, such as Python, Ruby, and Scala, is possible by adding a JAR to the classpath.
UDFs are part of the Cassandra schema, and are automatically propagated to all nodes in the cluster. UDFs can be overloaded, so that multiple UDFs with different argument types can have the same function name.
For example:
CREATE FUNCTION sample ( arg int ) ...;
CREATE FUNCTION sample ( arg text ) ...;
UDFs are susceptible to all of the normal problems with the chosen programming language. Accordingly, implementations should be safe against null pointer exceptions, illegal arguments, or any other potential source of exceptions. An exception during function execution will result in the entire statement failing. Valid queries for UDF use are SELECT
, INSERT
and UPDATE
statements.
Complex types like collections, tuple types and user-defined types are valid argument and return types in UDFs. Tuple types and user-defined types use the DataStax Java Driver conversion functions. Please see the Java Driver documentation for details on handling tuple types and user-defined types.
Arguments for functions can be literals or terms. Prepared statement placeholders can be used, too.
Note the use the double dollar-sign syntax to enclose the UDF source code.
For example:
CREATE FUNCTION some_function ( arg int )
RETURNS NULL ON NULL INPUT
RETURNS int
LANGUAGE java
AS $$ return arg; $$;
SELECT some_function(column) FROM atable ...;
UPDATE atable SET col = some_function(?) ...;
CREATE TYPE custom_type (txt text, i int);
CREATE FUNCTION fct_using_udt ( udtarg frozen )
RETURNS NULL ON NULL INPUT
RETURNS text
LANGUAGE java
AS $$ return udtarg.getString("txt"); $$;
The implicitly available udfContext
field (or binding for script UDFs) provides the necessary functionality to create new UDT and tuple values:
CREATE TYPE custom_type (txt text, i int);
CREATE FUNCTION fct\_using\_udt ( somearg int )
RETURNS NULL ON NULL INPUT
RETURNS custom_type
LANGUAGE java
AS $$
UDTValue udt = udfContext.newReturnUDTValue();
udt.setString("txt", "some string");
udt.setInt("i", 42);
return udt;
$$;
The definition of the UDFContext
interface can be found in the Apache Cassandra source code for org.apache.cassandra.cql3.functions.UDFContext
.
public interface UDFContext
{
UDTValue newArgUDTValue(String argName);
UDTValue newArgUDTValue(int argNum);
UDTValue newReturnUDTValue();
UDTValue newUDTValue(String udtName);
TupleValue newArgTupleValue(String argName);
TupleValue newArgTupleValue(int argNum);
TupleValue newReturnTupleValue();
TupleValue newTupleValue(String cqlDefinition);
}
Java UDFs already have some imports for common interfaces and classes defined. These imports are:
import java.nio.ByteBuffer;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.cassandra.cql3.functions.UDFContext;
import com.datastax.driver.core.TypeCodec;
import com.datastax.driver.core.TupleValue;
import com.datastax.driver.core.UDTValue;
Please note, that these convenience imports are not available for script UDFs.
CREATE FUNCTION statement
Creating a new user-defined function uses the CREATE FUNCTION
statement:
create_function_statement::= CREATE [ OR REPLACE ] FUNCTION [ IF NOT EXISTS]
function_name '(' arguments_declaration ')'
[ CALLED | RETURNS NULL ] ON NULL INPUT
RETURNS cql_type
LANGUAGE identifier
AS string arguments_declaration: identifier cql_type ( ',' identifier cql_type )*
For example:
CREATE OR REPLACE FUNCTION somefunction(somearg int, anotherarg text, complexarg frozen<someUDT>, listarg list)
RETURNS NULL ON NULL INPUT
RETURNS text
LANGUAGE java
AS $$
// some Java code
$$;
CREATE FUNCTION IF NOT EXISTS akeyspace.fname(someArg int)
CALLED ON NULL INPUT
RETURNS text
LANGUAGE java
AS $$
// some Java code
$$;
CREATE FUNCTION
with the optional OR REPLACE
keywords creates either a function or replaces an existing one with the same signature. A CREATE FUNCTION
without OR REPLACE
fails if a function with the same signature already exists. If the optional IF NOT EXISTS
keywords are used, the function will only be created only if another function with the same signature does not exist. OR REPLACE
and IF NOT EXISTS
cannot be used together.
Behavior for null
input values must be defined for each function:
RETURNS NULL ON NULL INPUT
declares that the function will always returnnull
if any of the input arguments isnull
.CALLED ON NULL INPUT
declares that the function will always be executed.
Function Signature
Signatures are used to distinguish individual functions. The signature consists of a fully-qualified function name of the <keyspace>.<function_name> and a concatenated list of all the argument types.
Note that keyspace names, function names and argument types are subject to the default naming conventions and case-sensitivity rules.
Functions belong to a keyspace; if no keyspace is specified, the current keyspace is used. User-defined functions are not allowed in the system keyspaces.
DROP FUNCTION statement
Dropping a function uses the DROP FUNCTION
statement:
drop_function_statement::= DROP FUNCTION [ IF EXISTS ] function_name [ '(' arguments_signature ')' ]
arguments_signature::= cql_type ( ',' cql_type )*
For example:
DROP FUNCTION myfunction;
DROP FUNCTION mykeyspace.afunction;
DROP FUNCTION afunction ( int );
DROP FUNCTION afunction ( text );
You must specify the argument types of the function, the arguments_signature, in the drop command if there are multiple overloaded functions with the same name but different signatures. DROP FUNCTION
with the optional IF EXISTS
keywords drops a function if it exists, but does not throw an error if it doesn’t.
Aggregate functions
Aggregate functions work on a set of rows. Values for each row are input, to return a single value for the set of rows aggregated.
If normal
columns, scalar functions
, UDT
fields, writetime
, or ttl
are selected together with aggregate functions, the values returned for them will be the ones of the first row matching the query.
Native aggregates
Count
The count
function can be used to count the rows returned by a query.
For example:
SELECT COUNT (*) FROM plays;
SELECT COUNT (1) FROM plays;
It also can count the non-null values of a given column:
SELECT COUNT (scores) FROM plays;
Max and Min
The max
and min
functions compute the maximum and the minimum value returned by a query for a given column.
For example:
SELECT MIN (players), MAX (players) FROM plays WHERE game = 'quake';
Sum
The sum
function sums up all the values returned by a query for a given column.
For example:
SELECT SUM (players) FROM plays;
Avg
The avg
function computes the average of all the values returned by a query for a given column.
For example:
SELECT AVG (players) FROM plays;
User-Defined Aggregates (UDAs)
User-defined aggregates allow the creation of custom aggregate functions. User-defined aggregates can be used in SELECT
statement.
Each aggregate requires an initial state of type STYPE
defined with the INITCOND`value (default value: `null
). The first argument of the state function must have type STYPE
. The remaining arguments of the state function must match the types of the user-defined aggregate arguments. The state function is called once for each row, and the value returned by the state function becomes the new state. After all rows are processed, the optional FINALFUNC
is executed with last state value as its argument.
The STYPE
value is mandatory in order to distinguish possibly overloaded versions of the state and/or final function, since the overload can appear after creation of the aggregate.
A complete working example for user-defined aggregates (assuming that a keyspace has been selected using the USE
statement):
CREATE OR REPLACE FUNCTION test.averageState(state tuple<int,bigint>, val int)
CALLED ON NULL INPUT
RETURNS tuple
LANGUAGE java
AS $$
if (val != null) {
state.setInt(0, state.getInt(0)+1);
state.setLong(1, state.getLong(1)+val.intValue());
}
return state;
$$;
CREATE OR REPLACE FUNCTION test.averageFinal (state tuple<int,bigint>)
CALLED ON NULL INPUT
RETURNS double
LANGUAGE java
AS $$
double r = 0;
if (state.getInt(0) == 0) return null;
r = state.getLong(1);
r /= state.getInt(0);
return Double.valueOf(r);
$$;
CREATE OR REPLACE AGGREGATE test.average(int)
SFUNC averageState
STYPE tuple
FINALFUNC averageFinal
INITCOND (0, 0);
CREATE TABLE test.atable (
pk int PRIMARY KEY,
val int
);
INSERT INTO test.atable (pk, val) VALUES (1,1);
INSERT INTO test.atable (pk, val) VALUES (2,2);
INSERT INTO test.atable (pk, val) VALUES (3,3);
INSERT INTO test.atable (pk, val) VALUES (4,4);
SELECT test.average(val) FROM atable;
CREATE AGGREGATE statement
Creating (or replacing) a user-defined aggregate function uses the CREATE AGGREGATE
statement:
create_aggregate_statement ::= CREATE [ OR REPLACE ] AGGREGATE [ IF NOT EXISTS ]
function_name '(' arguments_signature')'
SFUNC function_name
STYPE cql_type:
[ FINALFUNC function_name]
[ INITCOND term ]
See above for a complete example.
The CREATE AGGREGATE
command with the optional OR REPLACE
keywords creates either an aggregate or replaces an existing one with the same signature. A CREATE AGGREGATE
without OR REPLACE
fails if an aggregate with the same signature already exists. The CREATE AGGREGATE
command with the optional IF NOT EXISTS
keywords creates an aggregate if it does not already exist. The OR REPLACE
and IF NOT EXISTS
phrases cannot be used together.
The STYPE
value defines the type of the state value and must be specified. The optional INITCOND
defines the initial state value for the aggregate; the default value is null
. A non-null INITCOND
must be specified for state functions that are declared with RETURNS NULL ON NULL INPUT
.
The SFUNC
value references an existing function to use as the state-modifying function. The first argument of the state function must have type STYPE
. The remaining arguments of the state function must match the types of the user-defined aggregate arguments. The state function is called once for each row, and the value returned by the state function becomes the new state. State is not updated for state functions declared with RETURNS NULL ON NULL INPUT
and called with null
. After all rows are processed, the optional FINALFUNC
is executed with last state value as its argument. It must take only one argument with type STYPE
, but the return type of the FINALFUNC
may be a different type. A final function declared with RETURNS NULL ON NULL INPUT
means that the aggregate’s return value will be null
, if the last state is null
.
If no FINALFUNC
is defined, the overall return type of the aggregate function is STYPE
. If a FINALFUNC
is defined, it is the return type of that function.
DROP AGGREGATE statement
Dropping an user-defined aggregate function uses the DROP AGGREGATE
statement:
drop_aggregate_statement::= DROP AGGREGATE [ IF EXISTS ] function_name[ '(' arguments_signature ')'
]
For instance:
DROP AGGREGATE myAggregate;
DROP AGGREGATE myKeyspace.anAggregate;
DROP AGGREGATE someAggregate ( int );
DROP AGGREGATE someAggregate ( text );
The DROP AGGREGATE
statement removes an aggregate created using CREATE AGGREGATE
. You must specify the argument types of the aggregate to drop if there are multiple overloaded aggregates with the same name but a different signature.
The DROP AGGREGATE
command with the optional IF EXISTS
keywords drops an aggregate if it exists, and does nothing if a function with the signature does not exist.