This filter was introduced in MariaDB MaxScale 2.1.
Note: This filter has been deprecated in MaxScale 22.08.2 and will be removed in MaxScale 23.02.
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The insertstream filter converts bulk inserts into CSV data streams that are consumed by the backend server via the LOAD DATA LOCAL INFILE mechanism. This leverages the speed advantage of LOAD DATA LOCAL INFILE over regular inserts while also reducing the overall network traffic by condensing the inserted values into CSV.
Note: This is an experimental filter module
This filter has no parameters.
The filter translates all INSERT statements done inside an explicit transaction into LOAD DATA LOCAL INFILE streams. The file name used in the request will always be maxscale.data.
The following example is translated into a LOAD DATA LOCAL INFILE request followed by two CSV rows.
BEGIN;
INSERT INTO test.t1 VALUES (1, "hello"), (2, "world");
COMMIT;
Multiple inserts to the same table are combined into a single stream. This allows for efficient bulk loading with simple insert statements.
The following example will use only one LOAD DATA LOCAL INFILE request followed by four CSV rows.
BEGIN;
INSERT INTO test.t1 VALUES (1, "hello"), (2, "world");
INSERT INTO test.t1 VALUES (3, "foo"), (4, "bar");
COMMIT;
Non-INSERT statements executed inside the transaction will close the streaming of the data. Avoid interleaving SELECT statements with INSERT statements inside transactions.
The following example has to use two LOAD DATA LOCAL INFILE requests, each followed by two CSV rows.
Note: Avoid doing this!
BEGIN;
INSERT INTO test.t1 VALUES (1, "hello"), (2, "world");
SELECT * FROM test.t1;
INSERT INTO test.t1 VALUES (3, "foo"), (4, "bar");
COMMIT;
The more inserts that are streamed, the more efficient this filter is. The saving in network bandwidth in bytes can be estimated with the following formula:
((20 + t) * n) + (n * (m * 2)) - 108 - t = x
n = Number of INSERT statements
m = Number of values in each insert statement
t = Length of table name
x = Number of bytes saved
Positive values indicate savings in network bandwidth usage.
The filter has no parameters so it is extremely simple to configure. The following example shows the required filter configuration.
[Insert-Stream]
type=filter
module=insertstream