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KSQL Syntax Reference¶

KSQL has similar semantics to SQL:

Terminate KSQL statements with a semicolon ;.
Escape single-quote characters (') inside string literals by using two successive single quotes (''). For example, to escape 'T', write ''T''.

Terminology¶

When using KSQL, the following terminology is used.

Stream¶

A stream is an unbounded sequence of structured data (“facts”). For example, we could have a stream of financial transactions such as “Alice sent $100 to Bob, then Charlie sent $50 to Bob”. Facts in a stream are immutable, which means new facts can be inserted to a stream, but existing facts can never be updated or deleted. Streams can be created from an Apache Kafka® topic or derived from an existing stream. A stream’s underlying data is durably stored (persisted) within a Kafka topic on the Kafka brokers.

Table¶

A table is a view of a stream, or another table, and represents a collection of evolving facts. For example, we could have a table that contains the latest financial information such as “Bob’s current account balance is $150”. It is the equivalent of a traditional database table but enriched by streaming semantics such as windowing. Facts in a table are mutable, which means new facts can be inserted to the table, and existing facts can be updated or deleted. Tables can be created from a Kafka topic or derived from existing streams and tables. In both cases, a table’s underlying data is durably stored (persisted) within a Kafka topic on the Kafka brokers.

STRUCT¶

In KSQL 5.0 and higher, you can read nested data, in Avro and JSON formats, by using the STRUCT type in CREATE STREAM and CREATE TABLE statements. You can use the STRUCT type in these KSQL statements:

CREATE STREAM/TABLE (from a topic)
CREATE STREAM/TABLE AS SELECT (from existing streams/tables)
SELECT (non-persistent query)

Use the following syntax to declare nested data:

STRUCT<FieldName FieldType, ...>

The STRUCT type requires you to specify a list of fields. For each field, you specify the field name and field type. The field type can be any of the supported KSQL types, including the complex types MAP, ARRAY, and STRUCT.

Note

Properties is not a valid field name.

Here’s an example CREATE STREAM statement that uses a STRUCT to encapsulate a street address and a postal code:

CREATE STREAM orders (
  orderId BIGINT,
  address STRUCT<street VARCHAR, zip INTEGER>) WITH (...);

Access the fields in a STRUCT by using the dereference operator (->):

SELECT address->city, address->zip FROM orders;

For more info, see Operators.

Note

You can’t create new nested STRUCT data as the result of a query, but you can copy existing STRUCT fields as-is.

KSQL Time Units¶

The following list shows valid time units for the SIZE, ADVANCE BY, SESSION, and WITHIN clauses.

DAY, DAYS
HOUR, HOURS
MINUTE, MINUTES
SECOND, SECONDS
MILLISECOND, MILLISECONDS

For more information, see Windows in KSQL Queries.

KSQL Timestamp Formats¶

Time-based operations, like windowing, process records according to the timestamp in ROWTIME. By default, the implicit ROWTIME column is the timestamp of a message in a Kafka topic. Timestamps have an accuracy of one millisecond.

Use the TIMESTAMP property to override ROWTIME with the contents of the specified column. Define the format of a record’s timestamp by using the TIMESTAMP_FORMAT property.

If you use the TIMESTAMP property but don’t set TIMESTAMP_FORMAT, KSQL assumes that the timestamp field is a bigint. If you set TIMESTAMP_FORMAT, the TIMESTAMP field must be of type varchar and have a format that the DateTimeFormatter Java class can parse.

If your timestamp format has embedded single quotes, you can escape them by using two successive single quotes, ''. For example, to escape 'T', write ''T''. The following examples show how to escape the ' character in KSQL statements.

-- Example timestamp format: yyyy-MM-dd'T'HH:mm:ssX
CREATE STREAM TEST (ID bigint, event_timestamp VARCHAR)
  WITH (kafka_topic='test_topic',
        value_format='JSON',
        timestamp='event_timestamp',
        timestamp_format='yyyy-MM-dd''T''HH:mm:ssX');

-- Example timestamp format: yyyy.MM.dd G 'at' HH:mm:ss z
CREATE STREAM TEST (ID bigint, event_timestamp VARCHAR)
  WITH (kafka_topic='test_topic',
        value_format='JSON',
        timestamp='event_timestamp',
        timestamp_format='yyyy.MM.dd G ''at'' HH:mm:ss z');

-- Example timestamp format: hh 'o'clock' a, zzzz
CREATE STREAM TEST (ID bigint, event_timestamp VARCHAR)
  WITH (kafka_topic='test_topic',
        value_format='JSON',
        timestamp='event_timestamp',
        timestamp_format='hh ''o''clock'' a, zzzz');

For more information on timestamp formats, see DateTimeFormatter.

KSQL CLI Commands¶

The KSQL CLI commands can be run after starting the KSQL CLI. You can view the KSQL CLI help by running <path-to-confluent>/bin/ksql --help.

Tip: You can search and browse your command history in the KSQL CLI with Ctrl-R. After pressing Ctrl-R, start typing the command or any part of the command to show an auto-complete of past commands.

NAME
        ksql - KSQL CLI

SYNOPSIS
        ksql [ --config-file <configFile> ] [ {-h | --help} ]
                [ --output <outputFormat> ]
                [ --query-row-limit <streamedQueryRowLimit> ]
                [ --query-timeout <streamedQueryTimeoutMs> ] [--] <server>

OPTIONS
        --config-file <configFile>
            A file specifying configs for Ksql and its underlying Kafka Streams
            instance(s). Refer to KSQL documentation for a list of available
            configs.

        -h, --help
            Display help information

        --output <outputFormat>
            The output format to use (either 'JSON' or 'TABULAR'; can be changed
            during REPL as well; defaults to TABULAR)

        --query-row-limit <streamedQueryRowLimit>
            An optional maximum number of rows to read from streamed queries

            This options value must fall in the following range: value >= 1


        --query-timeout <streamedQueryTimeoutMs>
            An optional time limit (in milliseconds) for streamed queries

            This options value must fall in the following range: value >= 1


        --
            This option can be used to separate command-line options from the
            list of arguments (useful when arguments might be mistaken for
            command-line options)

        <server>
            The address of the Ksql server to connect to (ex:
            http://confluent.io:9098)

            This option may occur a maximum of 1 times

RUN SCRIPT¶

You can run a list of predefined queries and commands from in a file by using the RUN SCRIPT command.

Example:

RUN SCRIPT '/local/path/to/queries.sql';

The RUN SCRIPT command supports a subset of KSQL statements:

Persistent queries: CREATE STREAM, CREATE TABLE, CREATE STREAM AS SELECT, CREATE TABLE AS SELECT
DROP STREAM [IF EXISTS] [DELETE TOPIC]; and DROP TABLE [IF EXISTS] [DELETE TOPIC];
SET, UNSET statements
INSERT INTO statement

It does not support statements such as:

SHOW TOPICS and SHOW STREAMS etc
TERMINATE
Non-persistent queries: SELECT etc

RUN SCRIPT can also be used from the command line, for instance when writing shell scripts. For more information, see Running KSQL Statements From the Command Line.

KSQL data types¶

KSQL supports the following data types:

Primitive Types¶

KSQL supports the following primitive data types:

BOOLEAN
INTEGER or [INT]
BIGINT
DOUBLE
VARCHAR (or STRING)

Array¶

ARRAY<ElementType>

Note

The DELIMITED format doesn’t support arrays.

KSQL supports fields that are arrays of another type. All the elements in the array must be of the same type. The element type can be any valid KSQL type.

You can define arrays within a CREATE TABLE or CREATE STREAM statement by using the syntax ARRAY<ElementType>. For example, ARRAY<INT> defines an array of integers.

The elements of an array are zero-indexed and can be accessed by using the [] operator passing in the index. For example, SOME_ARRAY[0] retrieves the first element from the array. For more information, see Operators.

Map¶

MAP<KeyType, ValueType>

Note

The DELIMITED format doesn’t support maps.

KSQL supports fields that are maps. A map has a key and value type. All of the keys must be of the same type, and all of the values must be also be of the same type. Currently only STRING keys are supported. The value type can be any valid KSQL type.

You can define maps within a CREATE TABLE or CREATE STREAM statement by using the syntax MAP<KeyType, ValueType>. For example, MAP<STRING, INT> defines a map with string keys and integer values.

Access the values of a map by using the [] operator and passing in the key. For example, SOME_MAP['cost'] retrieves the value for the entry with key cost, or null For more information, see Operators.

Struct¶

STRUCT<FieldName FieldType, ...>

Note

The DELIMITED format doesn’t support structs.

KSQL supports fields that are structs. A struct represents strongly typed structured data. A struct is an ordered collection of named fields that have a specific type. The field types can be any valid KSQL type.

You can define a structs within a CREATE TABLE or CREATE STREAM statement by using the syntax STRUCT<FieldName FieldType, ...>. For example, STRUCT<ID BIGINT, NAME STRING, AGE INT> defines a struct with three fields, with the supplied name and type.

Access the fields of a struct by using the -> operator. For example, SOME_STRUCT->ID retrieves the value of the struct’s ID field. For more information, see Operators.

Decimal¶

DECIMAL(Precision, Scale)

KSQL supports fields that are numeric data types with fixed precision and scale:

Precision is the maximum total number of decimal digits to be stored, including values to the left and right of the decimal point. The precision must be greater than 1 - there is no default precision.
Scale is the number of decimal digits to the right of the decimal points. This number must be greater than 0 and less than or equal to the value for Precision.

Mathematical operations between DOUBLE and DECIMAL will automatically cause the decimal to be converted to a double value. Converting from decimal data type to any floating point type (DOUBLE) may cause loss of precision.

KSQL statements¶

Tip

KSQL statements must be terminated with a semicolon (;).
Statements can be spread over multiple lines.
The hyphen character, -, isn’t supported in names for streams, tables, topics, and columns.
Don’t use quotes around stream names or table names when you CREATE them.

Quoted identifiers for source and column names¶

Starting in KSQL 5.4, quoted identifiers in column names and source names are supported. If you have names that ksqlDB can’t parse, or if you need to control the case of your column names, enclose them in backtick characters, like this: `identifier`.

For example, a record with the following unparseable column names is still usable.

{"@id": 42, "col.val": value}

Use backtick characters to reference the columns:

-- Enclose unparseable column names with backticks:
CREATE STREAM s1 (`@id` integer, `col.val` string) …

Also, you can use backtick characters for the names of sources, like streams and tables. For example, you can create a stream name that has an embedded hyphen:

CREATE STREAM `foo-bar` (id VARCHAR) WITH (kafka_topic='foo', value_format='JSON', partitions=1);

You can use the hyphenated stream name in KSQL statements by enclosing it with backticks:

INSERT INTO `foo-bar` (id) VALUES ('123');
CREATE STREAM `foo-too` AS SELECT * FROM `foo-bar`;

 Message
------------------------------------------------------------------------------------
 Stream foo-too created and running. Created by query with query ID: CSAS_foo-too_5
------------------------------------------------------------------------------------

Note

By default, KSQL converts source and column names automatically to all capital letters. Use quoted identifiers to override this behavior and fully control your source and column names.

CREATE STREAM¶

Synopsis

CREATE STREAM stream_name ( { column_name data_type } [, ...] )
  WITH ( property_name = expression [, ...] );

Description

Create a new stream with the specified columns and properties. Columns can be any of the data types supported by KSQL.

KSQL adds the implicit columns ROWTIME and ROWKEY to every stream and table, which represent the corresponding Kafka message timestamp and message key, respectively. The timestamp has milliseconds accuracy.

The WITH clause supports the following properties:

Property	Description
KAFKA_TOPIC (required)	The name of the Kafka topic that backs this source. The topic must either already exist in Kafka, or PARTITIONS must be specified to create the topic. Command will fail if the topic exists with different partition/replica counts.
VALUE_FORMAT (required)	Specifies the serialization format of the message value in the topic. Supported formats: `JSON`, `DELIMITED` (comma-separated value), `AVRO` and `KAFKA`. For more information, see Formats.
PARTITIONS	The number of partitions in the backing topic. This property must be set if creating a STREAM without an existing topic (the command will fail if the topic does not exist).
REPLICAS	The number of replicas in the backing topic. If this property is not set but PARTITIONS is set, then the default Kafka cluster configuration for replicas will be used for creating a new topic.
VALUE_DELIMITER	Used when VALUE_FORMAT=’DELIMITED’. Supports single character to be a delimiter, defaults to ‘,’. For space and tab delimited values you must use the special values ‘SPACE’ or ‘TAB’, not an actual space or tab character.
KEY	Optimization hint: If the Kafka message key is also present as a field/column in the Kafka message value, you may set this property to associate the corresponding field/column with the implicit `ROWKEY` column (message key). If set, KSQL uses it as an optimization hint to determine if repartitioning can be avoided when performing aggregations and joins. You can only use this if the key format in Kafka is `VARCHAR` or `STRING`. Do not use this hint if the message key format in Kafka is `AVRO` or `JSON`. See Key Requirements for more information.
TIMESTAMP	By default, the implicit `ROWTIME` column is the timestamp of the message in the Kafka topic. The TIMESTAMP property can be used to override `ROWTIME` with the contents of the specified field/column within the Kafka message value (similar to timestamp extractors in Kafka’s Streams API). Timestamps have a millisecond accuracy. Time-based operations, such as windowing, will process a record according to the timestamp in `ROWTIME`.
TIMESTAMP_FORMAT	Used in conjunction with TIMESTAMP. If not set will assume that the timestamp field is a bigint. If it is set, then the TIMESTAMP field must be of type varchar and have a format that can be parsed with the java `DateTimeFormatter`. If your timestamp format has characters requiring single quotes, you can escape them with successive single quotes, `''`, for example: `'yyyy-MM-dd''T''HH:mm:ssX'`. For more information on timestamp formats, see DateTimeFormatter.
WRAP_SINGLE_VALUE	Controls how values are deserialized where the value schema contains only a single field. The setting controls how KSQL will deserialize the value of the records in the supplied `KAFKA_TOPIC` that contain only a single field. If set to `true`, KSQL expects the field to have been serialized as a named field within a record. If set to `false`, KSQL expects the field to have been serialized as an anonymous value. If not supplied, the system default, defined by ksql.persistence.wrap.single.values and defaulting to true`, is used. Note: `null` values have special meaning in KSQL. Care should be taken when dealing with single-field schemas where the value can be `null`. For more information, see Single field (un)wrapping. Note: Supplying this property for formats that do not support wrapping, for example `DELIMITED`, or when the value schema has multiple fields, will result in an error.
WINDOW_TYPE	By default, the topic is assumed to contain non-windowed data. If the data is windowed, i.e., was created using KSQL using a query that contains a `WINDOW` clause, then the `WINDOW_TYPE` property can be used to provide the window type. Valid values are `SESSION`, `HOPPING`, and `TUMBLING`.
WINDOW_SIZE	By default, the topic is assumed to contain non-windowed data. If the data is windowed, i.e., was created using KSQL using a query that contains a `WINDOW` clause, and the `WINDOW_TYPE` property is TUMBLING or HOPPING, then the WINDOW_SIZE property should be set. The property is a string with two literals, window size (a number) and window size unit (a time unit). For example: ‘10 SECONDS’.

For more information on timestamp formats, see DateTimeFormatter.

Note

To use Avro, you must have Schema Registry enabled and ksql.schema.registry.url must be set in the KSQL server configuration file. See Configuring Avro and Schema Registry for KSQL.
Avro field names are not case sensitive in KSQL. This matches the KSQL column name behavior.

Example:

CREATE STREAM pageviews (viewtime BIGINT, user_id VARCHAR, page_id VARCHAR)
  WITH (VALUE_FORMAT = 'JSON',
        KAFKA_TOPIC = 'my-pageviews-topic');

CREATE TABLE¶

Synopsis

CREATE TABLE table_name ( { column_name data_type } [, ...] )
  WITH ( property_name = expression [, ...] );

Description

Create a new table with the specified columns and properties. Columns can be any of the data types supported by KSQL.

KSQL adds the implicit columns ROWTIME and ROWKEY to every stream and table, which represent the corresponding Kafka message timestamp and message key, respectively. The timestamp has milliseconds accuracy.

When creating a table from a Kafka topic, KSQL requries the message key to be a VARCHAR aka STRING. If the message key is not of this type follow the instructions in Key Requirements.

The WITH clause supports the following properties:

Property	Description
KAFKA_TOPIC (required)	The name of the Kafka topic that backs this source. The topic must either already exist in Kafka, or PARTITIONS must be specified to create the topic. Command will fail if the topic exists with different partition/replica counts.
VALUE_FORMAT (required)	Specifies the serialization format of message values in the topic. Supported formats: `JSON`, `DELIMITED` (comma-separated value), `AVRO` and `KAFKA`. For more information, see Formats.
PARTITIONS	The number of partitions in the backing topic. This property must be set if creating a TABLE without an existing topic (the command will fail if the topic does not exist).
REPLICAS	The number of replicas in the backing topic. If this property is not set but PARTITIONS is set, then the default Kafka cluster configuration for replicas will be used for creating a new topic.
VALUE_DELIMITER	Used when VALUE_FORMAT=’DELIMITED’. Supports single character to be a delimiter, defaults to ‘,’. For space and tab delimited values you must use the special values ‘SPACE’ or ‘TAB’, not an actual space or tab character.
KEY	Optimization hint: If the Kafka message key is also present as a field/column in the Kafka message value, you may set this property to associate the corresponding field/column with the implicit `ROWKEY` column (message key). If set, KSQL uses it as an optimization hint to determine if repartitioning can be avoided when performing aggregations and joins. You can only use this if the key format in kafka is `VARCHAR` or `STRING`. Do not use this hint if the message key format in kafka is AVRO or JSON. For more information, see Key Requirements.
TIMESTAMP	By default, the implicit `ROWTIME` column is the timestamp of the message in the Kafka topic. The TIMESTAMP property can be used to override `ROWTIME` with the contents of the specified field/column within the Kafka message value (similar to timestamp extractors in Kafka’s Streams API). Timestamps have a millisecond accuracy. Time-based operations, such as windowing, will process a record according to the timestamp in `ROWTIME`.
TIMESTAMP_FORMAT	Used in conjunction with TIMESTAMP. If not set will assume that the timestamp field is a bigint. If it is set, then the TIMESTAMP field must be of type varchar and have a format that can be parsed with the Java `DateTimeFormatter`. If your timestamp format has characters requiring single quotes, you can escape them with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T''HH:mm:ssX'`. For more information on timestamp formats, see DateTimeFormatter.
WRAP_SINGLE_VALUE	Controls how values are deserialized where the values schema contains only a single field. The setting controls how KSQL will deserialize the value of the records in the supplied `KAFKA_TOPIC` that contain only a single field. If set to `true`, KSQL expects the field to have been serialized as named field within a record. If set to `false`, KSQL expects the field to have been serialized as an anonymous value. If not supplied, the system default, defined by ksql.persistence.wrap.single.values and defaulting to true`, is used. Note: `null` values have special meaning in KSQL. Care should be taken when dealing with single-field schemas where the value can be `null`. For more information, see Single field (un)wrapping. Note: Supplying this property for formats that do not support wrapping, for example `DELIMITED`, or when the value schema has multiple fields, will result in an error.
WINDOW_TYPE	By default, the topic is assumed to contain non-windowed data. If the data is windowed, i.e. was created using KSQL using a query that contains a `WINDOW` clause, then the `WINDOW_TYPE` property can be used to provide the window type. Valid values are `SESSION`, `HOPPING`, and `TUMBLING`.
WINDOW_SIZE	By default, the topic is assumed to contain non-windowed data. If the data is windowed, i.e., was created using KSQL using a query that contains a `WINDOW` clause, and the `WINDOW_TYPE` property is TUMBLING or HOPPING, then the WINDOW_SIZE property should be set. The property is a string with two literals, window size (a number) and window size unit (a time unit). For example: ‘10 SECONDS’.

Note

To use Avro, you must have Schema Registry enabled and ksql.schema.registry.url must be set in the KSQL server configuration file. See Configuring Avro and Schema Registry for KSQL.
Avro field names are not case sensitive in KSQL. This matches the KSQL column name behavior.

Example:

CREATE TABLE users (usertimestamp BIGINT, user_id VARCHAR, gender VARCHAR, region_id VARCHAR) WITH (
    KAFKA_TOPIC = 'my-users-topic',
    KEY = 'user_id');

CREATE STREAM AS SELECT¶

Synopsis

CREATE STREAM stream_name
  [WITH ( property_name = expression [, ...] )]
  AS SELECT  select_expr [, ...]
  FROM from_stream
  [ LEFT | FULL | INNER ] JOIN [join_table | join_stream] [ WITHIN [(before TIMEUNIT, after TIMEUNIT) | N TIMEUNIT] ] ON join_criteria
  [ WHERE condition ]
  [PARTITION BY column_name]
  EMIT CHANGES;

Description

Create a new stream along with the corresponding Kafka topic, and continuously write the result of the SELECT query into the stream and its corresponding topic.

If the PARTITION BY clause is present, then the resulting stream will have the specified column as its key. The column_name must be present in the select_expr. For more information, see Partition Data to Enable Joins.

For joins, the key of the resulting stream will be the value from the column from the left stream that was used in the join criteria. This column will be registered as the key of the resulting stream if included in the selected columns.

For stream-table joins, the column used in the join criteria for the table must be the table key.

For stream-stream joins, you must specify a WITHIN clause for matching records that both occur within a specified time interval. For valid time units, see KSQL Time Units.

For more information, see Join Event Streams with KSQL.

The WITH clause for the result supports the following properties:

Property	Description
KAFKA_TOPIC	The name of the Kafka topic that backs this stream. If this property is not set, then the name of the stream in upper case will be used as default.
VALUE_FORMAT	Specifies the serialization format of the message value in the topic. Supported formats: `JSON`, `DELIMITED` (comma-separated value), `AVRO` and `KAFKA`. If this property is not set, then the format of the input stream/table is used. For more information, see Formats.
VALUE_DELIMITER	Used when VALUE_FORMAT=’DELIMITED’. Supports single character to be a delimiter, defaults to ‘,’. For space and tab delimited values you must use the special values ‘SPACE’ or ‘TAB’, not an actual space or tab character.
PARTITIONS	The number of partitions in the backing topic. If this property is not set, then the number of partitions of the input stream/table will be used. In join queries, the property values are taken from the left-side stream or table. For KSQL 5.2 and earlier, if the property is not set, the value of the `ksql.sink.partitions` property, which defaults to four partitions, will be used. The `ksql.sink.partitions` property can be set in the properties file the KSQL server is started with, or by using the `SET` statement.
REPLICAS	The replication factor for the topic. If this property is not set, then the number of replicas of the input stream or table will be used. In join queries, the property values are taken from the left-side stream or table. For KSQL 5.2 and earlier, if the REPLICAS is not set, the value of the `ksql.sink.replicas` property, which defaults to one replica, will be used. The `ksql.sink.replicas` property can be set in the properties file the KSQL server is started with, or by using the `SET` statement.
TIMESTAMP	Sets a field within this stream’s schema to be used as the default source of `ROWTIME` for any downstream queries. Downstream queries that use time-based operations, such as windowing, will process records in this stream based on the timestamp in this field. By default, such queries will also use this field to set the timestamp on any records emitted to Kafka. Timestamps have a millisecond accuracy. If not supplied, the `ROWTIME` of the source stream will be used. Note: This doesn’t affect the processing of the query that populates this stream. For example, given the following statement: CREATE STREAM foo WITH (TIMESTAMP='t2') AS SELECT * FROM bar WINDOW TUMBLING (size 10 seconds) EMIT CHANGES; The window into which each row of `bar` is placed is determined by bar’s `ROWTIME`, not `t2`.
TIMESTAMP_FORMAT	Used in conjunction with TIMESTAMP. If not set will assume that the timestamp field is a bigint. If it is set, then the TIMESTAMP field must be of type varchar and have a format that can be parsed with the Java `DateTimeFormatter`. If your timestamp format has characters requiring single quotes, you can escape them with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T''HH:mm:ssX'`. For more information on timestamp formats, see DateTimeFormatter.
WRAP_SINGLE_VALUE	Controls how values are serialized where the values schema contains only a single field. The setting controls how the query will serialize values with a single-field schema. If set to `true`, KSQL will serialize the field as a named field within a record. If set to `false` KSQL, KSQL will serialize the field as an anonymous value. If not supplied, the system default, defined by ksql.persistence.wrap.single.values and defaulting to true`, is used. Note: `null` values have special meaning in KSQL. Care should be taken when dealing with single-field schemas where the value can be `null`. For more information, see Single field (un)wrapping. Note: Supplying this property for formats that do not support wrapping, for example `DELIMITED`, or when the value schema has multiple fields, will result in an error.

Note

To use Avro, you must have Schema Registry enabled and ksql.schema.registry.url must be set in the KSQL server configuration file. See Configuring Avro and Schema Registry for KSQL.
Avro field names are not case sensitive in KSQL. This matches the KSQL column name behavior.

Note

The KEY property is not supported – use PARTITION BY instead.

CREATE TABLE AS SELECT¶

Synopsis

CREATE TABLE table_name
  [WITH ( property_name = expression [, ...] )]
  AS SELECT  select_expr [, ...]
  FROM from_item
  [ LEFT | FULL | INNER ] JOIN join_table ON join_criteria
  [ WINDOW window_expression ]
  [ WHERE condition ]
  [ GROUP BY grouping_expression ]
  [ HAVING having_expression ]
  EMIT CHANGES;

Description

Create a new KSQL table along with the corresponding Kafka topic and stream the result of the SELECT query as a changelog into the topic. Note that the WINDOW clause can only be used if the from_item is a stream.

For joins, the key of the resulting table will be the value from the column from the left table that was used in the join criteria. This column will be registered as the key of the resulting table if included in the selected columns.

For joins, the columns used in the join criteria must be the keys of the tables being joined.

For more information, see Join Event Streams with KSQL.

The WITH clause supports the following properties:

Property	Description
KAFKA_TOPIC	The name of the Kafka topic that backs this table. If this property is not set, then the name of the table will be used as default.
VALUE_FORMAT	Specifies the serialization format of the message value in the topic. Supported formats: `JSON`, `DELIMITED` (comma-separated value), `AVRO` and `KAFKA`. If this property is not set, then the format of the input stream/table is used. For more information, see Formats.
VALUE_DELIMITER	Used when VALUE_FORMAT=’DELIMITED’. Supports single character to be a delimiter, defaults to ‘,’. For space and tab delimited values you must use the special values ‘SPACE’ or ‘TAB’, not an actual space or tab character.
PARTITIONS	The number of partitions in the backing topic. If this property is not set, then the number of partitions of the input stream/table will be used. In join queries, the property values are taken from the left-side stream or table. For KSQL 5.2 and earlier, if the property is not set, the value of the `ksql.sink.partitions` property, which defaults to four partitions, will be used. The `ksql.sink.partitions` property can be set in the properties file the KSQL server is started with, or by using the `SET` statement.
REPLICAS	The replication factor for the topic. If this property is not set, then the number of replicas of the input stream or table will be used. In join queries, the property values are taken from the left-side stream or table. For KSQL 5.2 and earlier, if the REPLICAS is not set, the value of the `ksql.sink.replicas` property, which defaults to one replica, will be used. The `ksql.sink.replicas` property can be set in the properties file the KSQL server is started with, or by using the `SET` statement.
TIMESTAMP	Sets a field within this tables’s schema to be used as the default source of `ROWTIME` for any downstream queries. Downstream queries that use time-based operations, such as windowing, will process records in this stream based on the timestamp in this field. Timestamps have a millisecond accuracy. If not supplied, the `ROWTIME` of the source stream will be used. Note: This doesn’t affect the processing of the query that populates this table. For example, given the following statement: CREATE TABLE foo WITH (TIMESTAMP='t2') AS SELECT host, COUNT(*) FROM bar WINDOW TUMBLING (size 10 seconds) GROUP BY host EMIT CHANGES; The window into which each row of `bar` is placed is determined by bar’s `ROWTIME`, not `t2`.
TIMESTAMP_FORMAT	Used in conjunction with TIMESTAMP. If not set will assume that the timestamp field is a bigint. If it is set, then the TIMESTAMP field must be of type varchar and have a format that can be parsed with the Java `DateTimeFormatter`. If your timestamp format has characters requiring single quotes, you can escape them with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T''HH:mm:ssX'`. For more information on timestamp formats, see DateTimeFormatter.
WRAP_SINGLE_VALUE	Controls how values are serialized where the values schema contains only a single field. The setting controls how the query will serialize values with a single-field schema. If set to `true`, KSQL will serialize the field as a named field within a record. If set to `false` KSQL, KSQL will serialize the field as an anonymous value. If not supplied, the system default, defined by ksql.persistence.wrap.single.values and defaulting to true`, is used. Note: `null` values have special meaning in KSQL. Care should be taken when dealing with single-field schemas where the value can be `null`. For more information, see Single field (un)wrapping. Note: Supplying this property for formats that do not support wrapping, for example `DELIMITED`, or when the value schema has multiple fields, will result in an error.

Note

To use Avro, you must have Schema Registry enabled and ksql.schema.registry.url must be set in the KSQL server configuration file. See Configuring Avro and Schema Registry for KSQL.
Avro field names are not case sensitive in KSQL. This matches the KSQL column name behavior.

CREATE TYPE¶

Synopsis

CREATE TYPE <type_name> AS <type>;

Description

Create an alias for a complex type declaration.

The CREATE TYPE statement registers a type alias directly in KSQL. Any types registered by using this command can be leveraged in future statements. The CREATE TYPE statement works in interactive and headless modes.

Any attempt to register the same type twice, without a corresponding DROP TYPE statement, will fail.

Example

CREATE TYPE ADDRESS AS STRUCT<number INTEGER, street VARCHAR, city VARCHAR>;

Use the ADDRESS custom type in a statement:

CREATE TYPE PERSON AS STRUCT<name VARCHAR, address ADDRESS>;

DROP TYPE¶

Synopsis

DROP TYPE <type_name>;

Description

The DROP TYPE statement removes a type alias from KSQL. This statement doesn’t fail if the type is in use in active queries or user-defined function, because the DROP TYPE statement doesn’t track whether queries are using the type. This means that you can drop a type any time, and old queries continue to work. Also, old queries running with a dropped type and don’t change if you register a new type with the same name.

Example

DROP TYPE ADDRESS;

SHOW TYPES¶

Synopsis

SHOW TYPES;

Description

The SHOW TYPES command lists all custom types and their type definitions.

Example

SHOW TYPES;

INSERT INTO¶

Synopsis

INSERT INTO stream_name
  SELECT select_expr [., ...]
  FROM from_stream
  [ WHERE condition ]
  [ PARTITION BY column_name ]
  EMIT CHANGES;

Description

Stream the result of the SELECT query into an existing stream and its underlying topic.

The schema and partitioning column produced by the query must match the stream’s schema and key, respectively. If the schema and partitioning column are incompatible with the stream, then the statement will return an error.

stream_name and from_item must both refer to a Stream. Tables are not supported.

Records written into the stream are not timestamp-ordered with respect to other queries. Therefore, the topic partitions of the output stream may contain out-of-order records even if the source stream for the query is ordered by timestamp.

INSERT VALUES¶

Synopsis

INSERT INTO <stream_name|table_name> [(column_name [, ...]])]
  VALUES (value [,...]);

Description

Produce a row into an existing stream or table and its underlying topic based on explicitly specified values. The first column_name of every schema is ROWKEY, which defines the corresponding Kafka key. If the source specifies a key and that column is present in the column names for this INSERT statement then that value and the ROWKEY value are expected to match, otherwise the value from ROWKEY will be copied into the value of the key column (or conversely from the key column into the ROWKEY column).

Any column not explicitly given a value is set to null. If no columns are specified, a value for every column is expected in the same order as the schema with ROWKEY as the first column. If columns are specified, the order does not matter.

Note

ROWTIME may be specified as an explicit column, but is not required when omitting the column specifications.

For example, the statements below would all be valid for a source with schema <KEY_COL VARCHAR, COL_A VARCHAR> with KEY=KEY_COL:

// inserts (1234, "key", "key", "A")
INSERT INTO foo (ROWTIME, ROWKEY, KEY_COL, COL_A) VALUES (1234, 'key', 'key', 'A');

// inserts (current_time(), "key", "key", "A")
INSERT INTO foo VALUES ('key', 'key', 'A');

// inserts (current_time(), "key", "key", "A")
INSERT INTO foo (KEY_COL, COL_A) VALUES ('key', 'A');

// inserts (current_time(), "key", "key", null)
INSERT INTO foo (KEY_COL) VALUES ('key');

The values will serialize using the value_format specified in the original CREATE statement. The key will always be serialized as a String.

DESCRIBE¶

Synopsis

DESCRIBE [EXTENDED] (stream_name|table_name);

Description

DESCRIBE: List the columns in a stream or table along with their data type and other attributes.
DESCRIBE EXTENDED: Display DESCRIBE information with additional runtime statistics, Kafka topic details, and the set of queries that populate the table or stream.

Extended descriptions provide the following metrics for the topic backing the source being described.

KSQL Metric	Description
consumer-failed-messages	Total number of failures during message consumption on the server.
consumer-messages-per-sec	The number of messages consumed per second from the topic by the server.
consumer-total-message-bytes	Total number of bytes consumed from the topic by the server.
consumer-total-messages	Total number of messages consumed from the topic by the server.
failed-messages-per-sec	Number of failures during message consumption (for example, deserialization failures) per second on the server.
last-failed	Time that the last failure occured when a message was consumed from the topic by the server.
last-message	Time that the last message was produced to or consumed from the topic by the server.
messages-per-sec	Number of messages produced per second into the topic by the server.
total-messages	Total number of messages produced into the topic by the server.
total-message-bytes	Total number of bytes produced into the topic by the server.

Example of describing a table:

DESCRIBE ip_sum;

Your output should resemble:

 Field   | Type
-------------------------------------
 ROWTIME | BIGINT           (system)
 ROWKEY  | VARCHAR(STRING)  (system)
 IP      | VARCHAR(STRING)  (key)
 KBYTES  | BIGINT
-------------------------------------
For runtime statistics and query details run: DESCRIBE EXTENDED <Stream,Table>

Example of describing a table with extended information:

DESCRIBE EXTENDED ip_sum;

Your output should resemble:

Type                 : TABLE
Key field            : CLICKSTREAM.IP
Timestamp field      : Not set - using <ROWTIME>
Key format           : STRING
Value format         : JSON
Kafka output topic   : IP_SUM (partitions: 4, replication: 1)

 Field   | Type
-------------------------------------
 ROWTIME | BIGINT           (system)
 ROWKEY  | VARCHAR(STRING)  (system)
 IP      | VARCHAR(STRING)  (key)
 KBYTES  | BIGINT
-------------------------------------

Queries that write into this TABLE
-----------------------------------
id:CTAS_IP_SUM - CREATE TABLE IP_SUM as SELECT ip,  sum(bytes)/1024 as kbytes FROM CLICKSTREAM window SESSION (300 second) GROUP BY ip EMIT CHANGES;

For query topology and execution plan run: EXPLAIN <QueryId>; for more information

Local runtime statistics
------------------------
messages-per-sec:      4.41   total-messages:       486     last-message: 12/14/17 4:32:23 PM GMT
 failed-messages:         0      last-failed:       n/a
(Statistics of the local KSQL server interaction with the Kafka topic IP_SUM)

DESCRIBE FUNCTION¶

Synopsis

DESCRIBE FUNCTION function_name;

Description

Provides a description of a function including input parameters and the return type.

EXPLAIN¶

Synopsis

EXPLAIN (sql_expression|query_id);

Description

Show the execution plan for a SQL expression or, given the ID of a running query, show the execution plan plus additional runtime information and metrics. Statements such as DESCRIBE EXTENDED, for example, show the IDs of queries related to a stream or table.

Example of explaining a running query:

EXPLAIN ctas_ip_sum;

Your output should resemble:

Type                 : QUERY
SQL                  : CREATE TABLE IP_SUM as SELECT ip,  sum(bytes)/1024 as kbytes FROM CLICKSTREAM window SESSION (300 second) GROUP BY ip EMIT CHANGES;


Local runtime statistics
------------------------
messages-per-sec:     104.38   total-messages:       14238     last-message: 12/14/17 4:30:42 PM GMT
 failed-messages:          0      last-failed:         n/a
(Statistics of the local Ksql Server interaction with the Kafka topic IP_SUM)

Execution plan
--------------
 > [ PROJECT ] Schema: [IP : STRING , KBYTES : INT64].
         > [ AGGREGATE ] Schema: [CLICKSTREAM.IP : STRING , CLICKSTREAM.BYTES : INT64 , KSQL_AGG_VARIABLE_0 : INT64].
                 > [ PROJECT ] Schema: [CLICKSTREAM.IP : STRING , CLICKSTREAM.BYTES : INT64].
                         > [ REKEY ] Schema: [CLICKSTREAM.ROWTIME : INT64 , CLICKSTREAM.ROWKEY : STRING , CLICKSTREAM._TIME : INT64 , CLICKSTREAM.TIME : STRING , CLICKSTREAM.IP : STRING , CLICKSTREAM.REQUEST : STRING , CLICKSTREAM.STATUS : INT32 , CLICKSTREAM.USERID : INT32 , CLICKSTREAM.BYTES : INT64 , CLICKSTREAM.AGENT : STRING].
                                 > [ SOURCE ] Schema: [CLICKSTREAM.ROWTIME : INT64 , CLICKSTREAM.ROWKEY : STRING , CLICKSTREAM._TIME : INT64 , CLICKSTREAM.TIME : STRING , CLICKSTREAM.IP : STRING , CLICKSTREAM.REQUEST : STRING , CLICKSTREAM.STATUS : INT32 , CLICKSTREAM.USERID : INT32 , CLICKSTREAM.BYTES : INT64 , CLICKSTREAM.AGENT : STRING].


Processing topology
-------------------
Sub-topologies:
  Sub-topology: 0
    Source: KSTREAM-SOURCE-0000000000 (topics: [clickstream])
      --> KSTREAM-MAP-0000000001
    Processor: KSTREAM-MAP-0000000001 (stores: [])
      --> KSTREAM-TRANSFORMVALUES-0000000002
      <-- KSTREAM-SOURCE-0000000000

DROP STREAM [IF EXISTS] [DELETE TOPIC];¶

Synopsis

DROP STREAM [IF EXISTS] stream_name [DELETE TOPIC];

Description

Drops an existing stream.

If the DELETE TOPIC clause is present, the stream’s source topic is marked for deletion, and if the topic format is AVRO, the corresponding Avro schema is deleted, too. Topic deletion is asynchronous, and actual removal from brokers may take some time to complete.

Note

DELETE TOPIC will not necessarily work if your kafka cluster is configured to create topics automatically with auto.create.topics.enable=true. We recommended checking after a few minutes to ensure that the topic was deleted.

If the IF EXISTS clause is present, the statement doesn’t fail if the table doesn’t exist.

DROP TABLE [IF EXISTS] [DELETE TOPIC];¶

Synopsis

DROP TABLE [IF EXISTS] table_name [DELETE TOPIC];

Description

Drops an existing table.

If the DELETE TOPIC clause is present, the table’s source topic is marked for deletion, and if the topic format is AVRO, the corresponding Avro schema is deleted in the schema registry. Topic deletion is asynchronous, and actual removal from brokers may take some time to complete.

Note

DELETE TOPIC will not necessarily work if your kafka cluster is configured to create topics automatically with auto.create.topics.enable=true. We recommended checking after a few minutes to ensure that the topic was deleted.

If the IF EXISTS clause is present, the statement doesn’t fail if the table doesn’t exist.

PRINT¶

PRINT qualifiedName [FROM BEGINNING] [INTERVAL interval] [LIMIT limit]

Description

Print the contents of Kafka topics to the KSQL CLI.

Important

SQL grammar defaults to uppercase formatting. You can use quotations (") to print topics that contain lowercase characters.

The PRINT statement supports the following properties:

Property	Description
FROM BEGINNING	Print starting with the first message in the topic. If not specified, PRINT starts with the most recent message.
INTERVAL interval	Print every `interval` th message. The default is 1, meaning that every message is printed.
LIMIT limit	Stop printing after `limit` messages. The default value is unlimited, requiring Ctrl+C to terminate the query.

For example:

PRINT 'ksql__commands' FROM BEGINNING;

Your output should resemble:

Format:JSON
{"ROWTIME":1516010696273,"ROWKEY":"\"stream/CLICKSTREAM/create\"","statement":"CREATE STREAM clickstream (_time bigint,time varchar, ip varchar, request varchar, status int, userid int, bytes bigint, agent varchar) with (kafka_topic = 'clickstream', value_format = 'json');","streamsProperties":{}}
{"ROWTIME":1516010709492,"ROWKEY":"\"table/EVENTS_PER_MIN/create\"","statement":"create table events_per_min as select userid, count(*) as events from clickstream window  TUMBLING (size 10 second) group by userid EMIT CHANGES;","streamsProperties":{}}
^CTopic printing ceased

PULL QUERY¶

Synopsis

SELECT select_expr [, ...]
  FROM aggregate_table
  WHERE ROWKEY=key
  [AND window_bounds];

Description

Pulls the current value from the materialized table and terminate. The result of this statement will not be persisted in a Kafka topic and will only be printed out in the console.

The WHERE clause must contain a single value of ROWKEY to retieve and may optionally include bounds on WINDOWSTART if the materialized table is windowed.

Example:

SELECT * FROM pageviews_by_region
  WHERE ROWKEY = 'Region_1'
    AND 1570051876000 <= WINDOWSTART AND WINDOWSTART <= 1570138276000;

When writing logical expressions using WINDOWSTART, ISO-8601 formatted datestrings can also be used to represent date times. For example, the above query is equivalent to the following:

SELECT * FROM pageviews_by_region
  WHERE ROWKEY = 'Region_1'
    AND '2019-10-02T21:31:16' <= WINDOWSTART AND WINDOWSTART <= '2019-10-03T21:31:16';

Timezones can be specified within the datestring. For example, 2017-11-17T04:53:45-0330 is in the Newfoundland time zone. If no timezone is specified within the datestring, then timestamps are interperted in the UTC timezone.

If not bounds are placed on WINDOWSTART then rows will be returned for all windows in the windowed table.

PUSH QUERY¶

Synopsis

SELECT select_expr [, ...]
  FROM from_item
  [ LEFT JOIN join_table ON join_criteria ]
  [ WINDOW window_expression ]
  [ WHERE condition ]
  [ GROUP BY grouping_expression ]
  [ HAVING having_expression ]
  EMIT CHANGES
  [ LIMIT count ];

Description

Push a continuous stream of updates to the KSQL stream or table. The result of this statement will not be persisted in a Kafka topic and will only be printed out in the console. To stop the continuous query in the CLI press Ctrl-C. Note that the WINDOW clause can only be used if the from_item is a stream.

In the above statements from_item is one of the following:

stream_name [ alias ]
table_name [ alias ]
from_item LEFT JOIN from_item ON join_condition

The WHERE clause can refer to any column defined for a stream or table, including the two implicit columns ROWTIME and ROWKEY.

Example:

SELECT * FROM pageviews
  WHERE ROWTIME >= 1510923225000
    AND ROWTIME <= 1510923228000;

When writing logical expressions using ROWTIME, ISO-8601 formatted datestrings can also be used to represent date times. For example, the above query is equivalent to the following:

SELECT * FROM pageviews
      WHERE ROWTIME >= '2017-11-17T04:53:45'
        AND ROWTIME <= '2017-11-17T04:53:48';

If the datestring is inexact, the rest of the timestamp is assumed to be padded with 0’s. For example, ROWTIME = '2019-07-30T11:00' is equivalent to ROWTIME = '2019-07-30T11:00:00.0000'.

Timezones can be specified within the datestring. For example, 2017-11-17T04:53:45-0330 is in the Newfoundland time zone. If no timezone is specified within the datestring, then timestamps are interperted in the UTC timezone.

A LIMIT can be used to limit the number of rows returned. Once the limit is reached the query will terminate.

Example:

SELECT * FROM pageviews EMIT CHANGES LIMIT 5;

If no limit is supplied the query will run until terminated, streaming back all results to the console.

Tip: If you want to select older data, you can configure KSQL to query the stream from the beginning. You must run this configuration before running the query:

SET 'auto.offset.reset' = 'earliest';

The WINDOW clause lets you control how to group input records that have the same key into so-called windows for operations such as aggregations or joins. Windows are tracked per record key. KSQL supports the following WINDOW types:

TUMBLING: Tumbling windows group input records into fixed-sized, non-overlapping windows based on the records’ timestamps. You must specify the window size for tumbling windows. Note: Tumbling windows are a special case of hopping windows where the window size is equal to the advance interval.

Example:
```
SELECT item_id, SUM(quantity)
  FROM orders
  WINDOW TUMBLING (SIZE 20 SECONDS)
  GROUP BY item_id
  EMIT CHANGES;
```
HOPPING: Hopping windows group input records into fixed-sized, (possibly) overlapping windows based on the records’ timestamps. You must specify the window size and the advance interval for hopping windows.

Example:
```
SELECT item_id, SUM(quantity)
  FROM orders
  WINDOW HOPPING (SIZE 20 SECONDS, ADVANCE BY 5 SECONDS)
  GROUP BY item_id
  EMIT CHANGES;
```
SESSION: Session windows group input records into so-called sessions. You must specify the session inactivity gap parameter for session windows. For example, imagine you set the inactivity gap to 5 minutes. If, for a given record key such as “alice”, no new input data arrives for more than 5 minutes, then the current session for “alice” is closed, and any newly arriving data for “alice” in the future will mark the beginning of a new session.

Example:
```
SELECT item_id, SUM(quantity)
  FROM orders
  WINDOW SESSION (20 SECONDS)
  GROUP BY item_id
  EMIT CHANGES;
```

Every output column of an expression in the SELECT list has an output name. To specify the output name of a column, use AS OUTPUT_NAME after the expression definition. If it is omitted, KSQL will assign a system generated name KSQL_COL_i where i is the ordinal number of the expression in the SELECT list. If the expression references a column of a from_item, then the output name is the name of that column.

Tip: KSQL will throw an error for duplicate output names. For example:

SELECT 1, KSQL_COL_0
  FROM orders
  EMIT CHANGES;

is not allowed as the output name for the literal 1 is KSQL_COL_0.

CAST¶

Synopsis

CAST (expression AS data_type);

You can cast an expression’s type to a new type using CAST. Here is an example of converting a BIGINT into a VARCHAR type:

-- This query converts the numerical count into a suffixed string; e.g., 5 becomes '5_HELLO'
SELECT page_id, CONCAT(CAST(COUNT(*) AS VARCHAR), '_HELLO')
  FROM pageviews_enriched
  WINDOW TUMBLING (SIZE 20 SECONDS)
  GROUP BY page_id
  EMIT CHANGES;

CASE¶

Synopsis

CASE
   WHEN condition THEN result
   [ WHEN ... THEN ... ]
   …
   [ WHEN … THEN … ]
   [ ELSE result ]
END

Currently, KSQL supports a searched form of CASE expression. In this form, CASE evaluates each boolean condition in WHEN clauses, from left to right. If a condition is true, CASE returns the corresponding result. If none of the conditions is true, CASE returns the result from the ELSE clause. If none of the conditions is true and there is no ELSE clause, CASE returns null.

The schema for all results must be the same, otherwise, KSQL rejects the statement. Here’s an example of a CASE expression:

SELECT
 CASE
   WHEN orderunits < 2.0 THEN 'small'
   WHEN orderunits < 4.0 THEN 'medium'
   ELSE 'large'
 END AS case_result
FROM orders
EMIT CHANGES;

LIKE¶

Synopsis

column_name LIKE pattern;

The LIKE operator is used for prefix or suffix matching. Currently KSQL supports %, which represents zero or more characters.

Example:

SELECT user_id
  FROM users
  WHERE user_id LIKE 'santa%'
  EMIT CHANGES;

BETWEEN¶

Synopsis

WHERE expression [NOT] BETWEEN start_expression AND end_expression;

The BETWEEN operator is used to indicate that a certain value must lie within a specified range, inclusive of boundaries. Currently, KSQL supports any expression that resolves to a numeric or string value for comparison.

Example:

SELECT event
  FROM events
  WHERE event_id BETWEEN 10 AND 20
  EMIT CHANGES;

SHOW FUNCTIONS¶

Synopsis

SHOW | LIST FUNCTIONS;

Description

List the available scalar and aggregate functions available.

SHOW TOPICS¶

Synopsis

SHOW | LIST TOPICS [EXTENDED];

Description

SHOW TOPICS lists the available topics in the Kafka cluster that KSQL is configured to connect to (default setting for bootstrap.servers: localhost:9092). SHOW TOPICS EXTENDED also displays consumer groups and their active consumer counts.

SHOW STREAMS¶

Synopsis

SHOW | LIST STREAMS;

Description

List the defined streams.

SHOW TABLES¶

Synopsis

SHOW | LIST TABLES;

Description

List the defined tables.

SHOW QUERIES¶

Synopsis

SHOW QUERIES;

Description

List the running persistent queries.

SHOW PROPERTIES¶

Synopsis

SHOW PROPERTIES;

Description

List the configuration settings that are currently in effect.

SPOOL¶

Synopsis

SPOOL <file_name|OFF>

Description

Stores issued commands and their results into a file. Only one spool may be active at a time and can be closed by issuing SPOOL OFF . Commands are prefixed with ksql> to differentiate from output.

TERMINATE¶

Synopsis

TERMINATE query_id;

Description

Terminate a persistent query. Persistent queries run continuously until they are explicitly terminated.

In client-server mode, exiting the CLI will not stop persistent queries because the KSQL server(s) will continue to process the queries.

(To terminate a non-persistent query use Ctrl-C in the CLI.)

Operators¶

KSQL supports the following operators in value expressions.

The explanation for each operator includes a supporting example based on the following table:

CREATE TABLE USERS (
    USERID BIGINT
    FIRST_NAME STRING,
    LAST_NAME STRING,
    NICKNAMES ARRAY<STRING>,
    ADDRESS STRUCT<STREET_NAME STRING, NUMBER INTEGER>
) WITH (KAFKA_TOPIC='users', VALUE_FORMAT='AVRO', KEY='USERID');

Arithmetic (+,-,/,*,%) The usual arithmetic operators may be applied to numeric types (INT, BIGINT, DOUBLE)

SELECT LEN(FIRST_NAME) + LEN(LAST_NAME) AS NAME_LENGTH FROM USERS EMIT CHANGES;

Concatenation (+,||) The concatenation operator can be used to concatenate STRING values.

SELECT FIRST_NAME + LAST_NAME AS FULL_NAME FROM USERS EMIT CHANGES;

You can use the + operator for multi-part concatenation, for example:

SELECT TIMESTAMPTOSTRING(ROWTIME, 'yyyy-MM-dd HH:mm:ss') +
        ': :heavy_exclamation_mark: On ' +
        HOST +
        ' there were ' +
        CAST(INVALID_LOGIN_COUNT AS VARCHAR) +
        ' attempts in the last minute (threshold is >=4)'
FROM INVALID_USERS_LOGINS_PER_HOST
WHERE INVALID_LOGIN_COUNT>=4
EMIT CHANGES;

Source Dereference (.) The source dereference operator can be used to specify columns by dereferencing the source stream or table.

SELECT USERS.FIRST_NAME FROM USERS EMIT CHANGES;

Subscript ([subscript_expr]) The subscript operator is used to reference the value at an array index or a map key.

SELECT NICKNAMES[0] FROM USERS EMIT CHANGES;

STRUCT dereference (->) Access nested data by declaring a STRUCT and using the dereference operator to access its fields:

CREATE STREAM orders (
  orderId BIGINT,
  address STRUCT<street VARCHAR, zip INTEGER>) WITH (...);

SELECT address->street, address->zip FROM orders EMIT CHANGES;

Combine -> with . when using aliases:

SELECT orders.address->street, o.address->zip FROM orders o EMIT CHANGES;

Scalar functions¶

Function	Example	Description
ABS	`ABS(col1)`	The absolute value of a value
ARRAYCONTAINS	`ARRAYCONTAINS('[1, 2, 3]', 3)`	Given JSON or AVRO array checks if a search value contains in it
AS_ARRAY	AS_ARRAY(col1, col2)`	Construct an array from a variable number of inputs.
AS_MAP	AS_MAP(keys, vals)`	Construct a map from a list of keys and a list of values.
CEIL	`CEIL(col1)`	The ceiling of a value.
CONCAT	`CONCAT(col1, '_hello')`	Concatenate two strings.
UNIX_DATE	`UNIX_DATE()`	Gets an integer representing days since epoch. The returned timestamp may differ depending on the local time of different KSQL Server instances.
UNIX_TIMESTAMP	`UNIX_TIMESTAMP()`	Gets the Unix timestamp in milliseconds, represented as a BIGINT. The returned timestamp may differ depending on the local time of different KSQL Server instances.
DATETOSTRING	`DATETOSTRING(START_DATE, 'yyyy-MM-dd')`	Converts an integer representation of a date into a string representing the date in the given format. Single quotes in the timestamp format can be escaped with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T'''`. The integer represents days since epoch matching the encoding used by Kafka Connect dates.
ELT	`ELT(n INTEGER, args VARCHAR[])`	Returns element `n` in the `args` list of strings, or NULL if `n` is less than 1 or greater than the number of arguments. This function is 1-indexed. ELT is the complement to FIELD.
ENTRIES	`ENTRIES(map MAP, sorted BOOLEAN)`	Constructs an array of structs from the entries in a map. Each struct has a field with name `K` containing the key which is a String and a field with name `V` holding the value. If `sorted` is true the entries will be sorted by key.
EXTRACTJSONFIELD	`EXTRACTJSONFIELD(message, '$.log.cloud')`	Given a string column in JSON format, extract the field that matches. Example where EXTRACTJSONFIELD is needed: `{"foo": \"{\"bar\": \"quux\"}\"}` However, in cases where the column is really an object but declared as a STRING you can use the `STRUCT` type, which is easier to work with. Example where `STRUCT` will work: `{"foo": {"bar": "quux"}}`
EXP	`EXP(col1)`	The exponential of a value.
FIELD	`FIELD(str VARCHAR, args VARCHAR[])`	Returns the 1-indexed position of `str` in `args`, or 0 if not found. If `str` is NULL, the return value is 0, because NULL is not considered to be equal to any value. FIELD is the complement to ELT.
FLOOR	`FLOOR(col1)`	The floor of a value.
GENERATE_SERIES	`GENERATE_SERIES(start, end)`	Constructs an array of values between `start` and `end` (inclusive). Parameters can be `INT` or `BIGINT`.
GENERATE_SERIES	`GENERATE_SERIES(start, end, step)`	Constructs an array of values between `start` and `end` (inclusive) with a specified step size. Step can be positive or negative. Parameters `start` and `end` can be `INT` or `BIGINT`. Parameter `step` must be an `INT`.
GEO_DISTANCE	`GEO_DISTANCE(lat1, lon1, lat2, lon2, unit)`	The great-circle distance between two lat-long points, both specified in decimal degrees. An optional final parameter specifies `KM` (the default) or `miles`.
IFNULL	`IFNULL(col1, retval)`	If the provided VARCHAR is NULL, return `retval`, otherwise, return the value. Only VARCHAR values are supported for the input. The return value must be a VARCHAR.
INITCAP	`INITCAP(col1)`	Capitalize the first letter in each word and convert all other letters to lowercase. Words are delimited by whitespace.
LCASE	`LCASE(col1)`	Convert a string to lowercase.
LEN	`LEN(col1)`	The length of a string.
LN	`LN(col1)`	The natural logarithm of a value.
MASK	`MASK(col1, 'X', 'x', 'n', '-')`	Convert a string to a masked or obfuscated version of itself. The optional arguments following the input string to be masked are the characters to be substituted for upper-case, lower-case, numeric and other characters of the input, respectively. If the mask characters are omitted then the default values, illustrated in the example to the left, will be applied. Set a given mask character to NULL to prevent any masking of that character type. For example: `MASK("My Test $123")` will return `Xx-Xxxx--nnn`, applying all default masks. `MASK("My Test $123", '', NULL, '1', NULL)` will yield `y *est $111`.
MASK_KEEP_LEFT	`MASK_KEEP_LEFT(col1, numChars, 'X', 'x', 'n', '-')`	Similar to the `MASK` function above, except that the first or left-most `numChars` characters will not be masked in any way. For example: `MASK_KEEP_LEFT("My Test $123", 4)` will return `My Txxx--nnn`.
MASK_KEEP_RIGHT	`MASK_KEEP_RIGHT(col1, numChars, 'X', 'x', 'n', '-')`	Similar to the `MASK` function above, except that the last or right-most `numChars` characters will not be masked in any way. For example:`MASK_KEEP_RIGHT("My Test $123", 4)` will return `Xx-Xxxx-$123`.
MASK_LEFT	`MASK_LEFT(col1, numChars, 'X', 'x', 'n', '-')`	Similar to the `MASK` function above, except that only the first or left-most `numChars` characters will have any masking applied to them. For example: `MASK_LEFT("My Test $123", 4)` will return `Xx-Xest $123`.
MASK_RIGHT	`MASK_RIGHT(col1, numChars, 'X', 'x', 'n', '-')`	Similar to the `MASK` function above, except that only the last or right-most `numChars` characters will have any masking applied to them. For example: `MASK_RIGHT("My Test $123", 4)` will return `My Test -nnn`.
RANDOM	`RANDOM()`	Return a random DOUBLE value between 0.0 and 1.0.
REPLACE	`REPLACE(col1, 'foo', 'bar')`	Replace all instances of a substring in a string with a new string.
ROUND	`ROUND(col1)` or `ROUND(col1, scale)`	Round a value to the number of decimal places as specified by scale to the right of the decimal point. If scale is negative then value is rounded to the right of the decimal point. Numbers equidistant to the nearest value are rounded up (in the positive direction). If the number of decimal places is not provided it defaults to zero.
SIGN	`SIGN(col1)`	The sign of a numeric value as an INTEGER: * -1 if the argument is negative * 0 if the argument is zero * 1 if the argument is positive * `null` argument is null
SQRT	`SQRT(col1)`	The square root of a value.
SLICE	`SLICE(col1, from, to)`	Slices a list based on the supplied indices. The indices start at 1 and include both endpoints.
SPLIT	`SPLIT(col1, delimiter)`	Splits a string into an array of substrings based on a delimiter. If the delimiter is not found, then the original string is returned as the only element in the array. If the delimiter is empty, then all characters in the string are split. If either, string or delimiter, are NULL, then a NULL value is returned. If the delimiter is found at the beginning or end of the string, or there are contiguous delimiters, then an empty space is added to the array.
STRINGTODATE	`STRINGTODATE(col1, 'yyyy-MM-dd')`	Converts a string representation of a date in the given format into an integer representing days since epoch. Single quotes in the timestamp format can be escaped with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T'''`.
STRINGTOTIMESTAMP	`STRINGTOTIMESTAMP(col1, 'yyyy-MM-dd HH:mm:ss.SSS' [, TIMEZONE])`	Converts a string value in the given format into the BIGINT value that represents the millisecond timestamp. Single quotes in the timestamp format can be escaped with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T''HH:mm:ssX'`. TIMEZONE is an optional parameter and it is a java.util.TimeZone ID format, for example: “UTC”, “America/Los_Angeles”, “PST”, “Europe/London”. For more information on timestamp formats, see DateTimeFormatter.
SUBSTRING	`SUBSTRING(col1, 2, 5)`	`SUBSTRING(str, pos, [len]`. Returns a substring of `str` that starts at `pos` (first character is at position 1) and has length `len`, or continues to the end of the string. For example, `SUBSTRING("stream", 1, 4)` returns “stre”. NOTE: Prior to v5.1 of KSQL the syntax was: `SUBSTRING(str, start, [end])`, where `start` and `end` positions where base-zero indexes (first character at position 0) to start (inclusive) and end (exclusive) the substring, respectively. For example, `SUBSTRING("stream", 1, 4)` would return “tre”. It is possible to switch back to this legacy mode by setting `ksql.functions.substring.legacy.args` to `true`. We recommend against enabling this setting. Instead, update your queries accordingly.
TIMESTAMPTOSTRING	`TIMESTAMPTOSTRING(ROWTIME, 'yyyy-MM-dd HH:mm:ss.SSS' [, TIMEZONE])`	Converts a BIGINT millisecond timestamp value into the string representation of the timestamp in the given format. Single quotes in the timestamp format can be escaped with two successive single quotes, `''`, for example: `'yyyy-MM-dd''T''HH:mm:ssX'`. TIMEZONE is an optional parameter and it is a java.util.TimeZone ID format, for example: “UTC”, “America/Los_Angeles”, “PST”, “Europe/London”. For more information on timestamp formats, see DateTimeFormatter.
TRIM	`TRIM(col1)`	Trim the spaces from the beginning and end of a string.
UCASE	`UCASE(col1)`	Convert a string to uppercase.
URL_DECODE_PARAM	`URL_DECODE_PARAM(col1)`	Unescapes the URL-param-encoded value in `col1` This is the inverse of URL_ENCODE_PARAM ^* Input: `'url%20encoded` Output: `url encoded`
URL_ENCODE_PARAM	`URL_ENCODE_PARAM(col1)`	Escapes the value of `col1` such that it can safely be used in URL query parameters. Note that this is not the same as encoding a value for use in the path portion of a URL. Input: `url encoded` Output: `'url%20encoded`
URL_EXTRACT_FRAGMENT	`URL_EXTRACT_FRAGMENT(url)`	Extract the fragment portion of the specified value. Returns NULL if `url` is not a valid URL or if the fragment does not exist. Any encoded value will be decoded. Input: `http://test.com#frag`, Output: `frag` Input: `http://test.com#frag%20space`, Output: `frag space`
URL_EXTRACT_HOST	`URL_EXTRACT_HOST(url)`	Extract the host-name portion of the specified value. Returns NULL if the `url` is not a valid URI according to RFC-2396. Input: `http://test.com:8080/path`, Output: `test.com`
URL_EXTRACT_PARAMETER	`URL_EXTRACT_PARAMETER(url, parameter_name)`	Extract the value of the requested parameter from the query-string of `url`. Returns NULL if the parameter is not present, has no value specified for it in the query-string, or `url` is not a valid URI. Encodes the param and decodes the output (see examples). To get all of the parameter values from a URL as a single string, see `URL_EXTRACT_QUERY.` Input: `http://test.com?a%20b=c%20d`, `a b` Output: `c d` Input: `http://test.com?a=foo&b=bar`, b Output: `bar`
URL_EXTRACT_PATH	`URL_EXTRACT_PATH(url)`	Extracts the path from `url`. Returns NULL if `url` is not a valid URI but returns an empty string if the path is empty. Input: `http://test.com/path/to#a` Output: `path/to`
URL_EXTRACT_PORT	`URL_EXTRACT_PORT(url)`	Extract the port number from `url`. Returns NULL if `url` is not a valid URI or does not contain an explicit port number. Input: `http://localhost:8080/path` Output: `8080`
URL_EXTRACT_PROTOCOL	`URL_EXTRACT_PROTOCOL(url)`	Extract the protocol from `url`. Returns NULL if `url` is an invalid URI or has no protocol. Input: `http://test.com?a=foo&b=bar` Output: `http`
URL_EXTRACT_QUERY	`URL_EXTRACT_QUERY(url)`	Extract the decoded query-string portion of `url`. Returns NULL if no query-string is present or `url` is not a valid URI. Input: `http://test.com?a=foo%20bar&b=baz`, Output: `a=foo bar&b=baz`

^* All KSQL URL functions assume URI syntax defined in RFC 39386. For more information on the structure of a URI, including definitions of the various components, see Section 3 of the RFC. For encoding/decoding, the application/x-www-form-urlencoded convention is followed.

Aggregate functions¶

Function	Example	Input Type	Description
COLLECT_LIST	`COLLECT_LIST(col1)`	Stream, Table	Return an array containing all the values of `col1` from each input row (for the specified grouping and time window, if any). Currently only works for simple types (not Map, Array, or Struct). This version limits the size of the result Array to a maximum of 1000 entries and any values beyond this limit are silently ignored. When using with a window type of `session`, it can sometimes happen that two session windows get merged together into one when a late-arriving record with a timestamp between the two windows is processed. In this case the 1000 record limit is calculated by first considering all the records from the first window, then the late-arriving record, then the records from the second window in the order they were originally processed.
COLLECT_SET	`COLLECT_SET(col1)`	Stream	Return an array containing the distinct values of `col1` from each input row (for the specified grouping and time window, if any). Currently only works for simple types (not Map, Array, or Struct). This version limits the size of the result Array to a maximum of 1000 entries and any values beyond this limit are silently ignored. When using with a window type of `session`, it can sometimes happen that two session windows get merged together into one when a late-arriving record with a timestamp between the two windows is processed. In this case the 1000 record limit is calculated by first considering all the records from the first window, then the late-arriving record, then the records from the second window in the order they were originally processed.
COUNT	`COUNT(col1)`, `COUNT(*)`	Stream, Table	Count the number of rows. When `col1` is specified, the count returned will be the number of rows where `col1` is non-null. When `*` is specified, the count returned will be the total number of rows.
HISTOGRAM	`HISTOGRAM(col1)`	Stream, Table	Return a map containing the distinct String values of `col1` mapped to the number of times each one occurs for the given window. This version limits the number of distinct values which can be counted to 1000, beyond which any additional entries are ignored. When using with a window type of `session`, it can sometimes happen that two session windows get merged together into one when a late-arriving record with a timestamp between the two windows is processed. In this case the 1000 record limit is calculated by first considering all the records from the first window, then the late-arriving record, then the records from the second window in the order they were originally processed.
AVERAGE	`AVG(col1)`	Stream, Table	Return the average value for a given column. Note: rows where `col1` is null are ignored.
MAX	`MAX(col1)`	Stream	Return the maximum value for a given column and window. Note: rows where `col1` is null will be ignored.
MIN	`MIN(col1)`	Stream	Return the minimum value for a given column and window. Note: rows where `col1` is null will be ignored.
SUM	`SUM(col1)`	Stream, Table	Sums the column values Note: rows where `col1` is null will be ignored.
TOPK	`TOPK(col1, k)`	Stream	Return the Top K values for the given column and window Note: rows where `col1` is null will be ignored.
TOPKDISTINCT	`TOPKDISTINCT(col1, k)`	Stream	Return the distinct Top K values for the given column and window Note: rows where `col1` is null will be ignored.
WindowStart	`WindowStart()`	Stream Table	Extract the start time of the current window, in milliseconds. If the query is not windowed the function will return null.
WindowEnd	`WindowEnd()`	Stream Table	Extract the end time of the current window, in milliseconds. If the query is not windowed the function will return null.

For more information, see Aggregate Streaming Data With KSQL.

Table functions¶

Function	Example	Input Type	Description
EXPLODE	`EXPLODE(col1)`	Array	This function takes an Array and outputs one value for each of the elements of the array. The output values have the same type as the array elements.

For more information, see Using Table Functions With KSQL.

Key Requirements¶

Message Keys¶

The CREATE STREAM and CREATE TABLE statements, which read data from a Kafka topic into a stream or table, allow you to specify a field/column in the Kafka message value that corresponds to the Kafka message key by setting the KEY property of the WITH clause.

Example:

CREATE TABLE users (registertime BIGINT, gender VARCHAR, regionid VARCHAR, userid VARCHAR)
  WITH (KAFKA_TOPIC='users', VALUE_FORMAT='JSON', KEY = 'userid');

The KEY property is optional. KSQL uses it as an optimization hint to determine if repartitioning can be avoided when performing aggregations and joins.

Important

Don’t set the KEY property, unless you have validated that your stream doesn’t need to be re-partitioned for future joins. If you set the KEY property, you will need to re-partition explicitly if your record key doesn’t meet partitioning requirements. For more information, see Partition Data to Enable Joins.

In either case, when setting KEY you must be sure that both of the following conditions are true:

For every record, the contents of the Kafka message key must be the same as the contents of the column set in KEY (which is derived from a field in the Kafka message value).
KEY must be set to a column of type VARCHAR aka STRING.

If these conditions are not met, then the results of aggregations and joins may be incorrect. However, if your data doesn’t meet these requirements, you can still use KSQL with a few extra steps. The following section explains how.

Table-table joins can be joined only on the KEY field, and one-to-many (1:N) joins aren’t supported.

What To Do If Your Key Is Not Set or Is In A Different Format¶

Streams¶

For streams, just leave out the KEY property from the WITH clause. KSQL will take care of repartitioning the stream for you using the value(s) from the GROUP BY columns for aggregates, and the join predicate for joins.

Tables¶

For tables, you can still use KSQL if the message key is not also present in the Kafka message value or if it is not in the required format as long as one of the following statements is true:

The message key is a unary function of the value in the desired key column.
It is ok for the messages in the topic to be re-ordered before being inserted into the table.

First create a stream to have KSQL write the message key, and then declare the table on the output topic of this stream:

Example:

Goal: You want to create a table from a topic, which is keyed by userid of type INT.
Problem: The message key is present as a field/column (aptly named userid) in the message value but in the wrong format (INT instead of VARCHAR).

-- Create a stream on the original topic
CREATE STREAM users_with_wrong_key_format (userid INT, username VARCHAR, email VARCHAR)
  WITH (KAFKA_TOPIC='users', VALUE_FORMAT='JSON');

-- Derive a new stream with the required key changes.
-- 1) The CAST statement converts the key to the required format.
-- 2) The PARTITION BY clause re-partitions the stream based on the new, converted key.
CREATE STREAM users_with_proper_key
  WITH(KAFKA_TOPIC='users-with-proper-key') AS
  SELECT CAST(userid as VARCHAR) as userid_string, username, email
  FROM users_with_wrong_key_format
  PARTITION BY userid_string
  EMIT CHANGES;

-- Now you can create the table on the properly keyed stream.
CREATE TABLE users_table (userid_string VARCHAR, username VARCHAR, email VARCHAR)
  WITH (KAFKA_TOPIC='users-with-proper-key',
        VALUE_FORMAT='JSON',
        KEY='userid_string');

Example:

Goal: You want to create a table from a topic, which is keyed by userid of type INT.
Problem: The message key is not present as a field/column in the topic’s message values.

-- Create a stream on the original topic.
-- The topic is keyed by userid, which is available as the implicit column ROWKEY
-- in the users_with_missing_key stream. Note how the explicit column definitions
-- only define username and email but not userid.
CREATE STREAM users_with_missing_key (username VARCHAR, email VARCHAR)
  WITH (KAFKA_TOPIC='users', VALUE_FORMAT='JSON');

-- Derive a new stream with the required key changes.
-- 1) The contents of ROWKEY (message key) are copied into the message value as the userid_string column,
--    and the CAST statement converts the key to the required format.
-- 2) The PARTITION BY clause re-partitions the stream based on the new, converted key.
CREATE STREAM users_with_proper_key
  WITH(KAFKA_TOPIC='users-with-proper-key') AS
  SELECT CAST(ROWKEY as VARCHAR) as userid_string, username, email
  FROM users_with_missing_key
  PARTITION BY userid_string
  EMIT CHANGES;

-- Now you can create the table on the properly keyed stream.
CREATE TABLE users_table (userid_string VARCHAR, username VARCHAR, email VARCHAR)
  WITH (KAFKA_TOPIC='users-with-proper-key',
        VALUE_FORMAT='JSON',
        KEY='userid_string');

For more information, see Partition Data to Enable Joins.