Fluent Bit + SQL

You can find the detailed query language syntax in BNF form here. The following section will be a brief introduction on how to write SQL queries for Fluent Bit stream processing.

Synopsis

Description

Select keys from records coming from a stream or records matching a specific Tag pattern. Note that a simple statement not associated from a stream creation will send the results to the standard output interface (stdout), useful for debugging purposes.

The query allows filtering the results by applying a condition using WHERE statement. We will explain WINDOW and GROUP BY statements later in aggregation functions section.

Examples

Select all keys from records coming from a stream called apache:

SELECT * FROM STREAM:apache;

Select all keys from records which Tag starts with apache.:

SELECT code AS http_status FROM TAG:'apache.*';

CREATE STREAM Statement

Synopsis

CREATE STREAM stream_name
  [WITH (property_name=value, [...])]
  AS select_statement

Description

Create a new stream of data using the results from the SELECT statement. New stream created can be optionally re-ingested back into Fluent Bit pipeline if the property Tag is set in the WITH statement.

Examples

Create a new stream called hello from stream called apache:

CREATE STREAM hello AS SELECT * FROM TAG:'apache.*';

Aggregation functions are used in results_statement on the keys, allowing to perform data calculation on groups of records. Group of records that aggregation functions apply on are determined by WINDOW keyword. When WINDOW is not specified, aggregation functions apply on the current buffer of records received, which may have non-deterministic number of elements. Aggregation functions can be applied on records in a window of a specific time interval (see the syntax of WINDOW in select statement).

Fluent Bit streaming currently supports tumbling window, which is non-overlapping window type. That means, a window of size 5 seconds performs aggregation computations on records over a 5-second interval, and then starts new calculations for the next interval.

In addition, the syntax support GROUP BY statement, which groups the results by the one or more keys, when they have the same values.

AVG

Synopsis

Description

Calculates the average of request sizes in POST requests.

Synopsis

SELECT host, COUNT(*) FROM STREAM:apache WINDOW TUMBLING (5 SECOND) GROUP BY host;

Description

Count the number of records in 5 second windows group by host IP addresses.

MIN

Synopsis

SELECT MIN(key) FROM STREAM:apache;

Description

Gets the minimum value of a key in a set of records.

MAX

Synopsis

SELECT MIN(key) FROM STREAM:apache;

Description

Gets the maximum value of a key in a set of records.

Synopsis

Description

Calculates the sum of all values of key in a set of records.

NOW

Synopsis

SELECT NOW() FROM STREAM:apache;

Description

Add system time using format: %Y-%m-%d %H:%M:%S. Output example: 2019-03-09 21:36:05.

UNIX_TIMESTAMP

Synopsis

Description

Add current Unix timestamp to the record. Output example: 1552196165 .

Record functions append new keys to the record using values from the record context.

Synopsis

SELECT RECORD_TAG() FROM STREAM:apache;

Description

Append Tag string associated to the record as a new key.

RECORD_TIME

Synopsis

SELECT RECORD_TIME() FROM STREAM:apache;

Similar to conventional SQL statements, WHERE condition is supported in Fluent Bit query language. The language supports conditions over keys and subkeys, for instance:

SELECT AVG(size) FROM STREAM:apache WHERE method = 'POST' AND status = 200;

It is possible to check the existence of a key in the record using record-specific function @record.contains:

SELECT MAX(key) FROM STREAM:apache WHERE @record.contains(key);

And to check if the value of a key is/is not NULL:

Description

Append a new key with the record Timestamp in double format: seconds.nanoseconds. Output example: 1552196165.705683 .