Category Archives: Logical Decoding

PostgreSQL 9.4 released

It looks like PostgreSQL 9.4 was released last Thursday. I’ve been keeping an eye on 9.4 and watching some of the chat about new features, although I’ve just been too buried in work to pay too much attention. Today however is my first day off for Christmas, so finally I’ve got some time to look into it.

The most interesting features to me are jsonb and Logical Decoding, so that’s what I’m going to look at, but there’s more and you can read about it here.

jsonb

The new jsonb data type stores JSON data internally in a binary form, which makes it possible to index the keys and values within. In previous versions we have a JSON data type but all that does is enforce valid JSON; the data is still stored as text. Whilst it is possible to do lookups on key-value data in previous versions using the hstore type (provided by the hstore module), with JSON seemingly being ubiquitous in aplications these days jsonb means we can just let devs store their data straight into the database and still be able to do fast lookups and searches.

At work we get quite a lot of variable callback data from web APIs, or serialized data from application objects that tends to end up being stored as text. The ability to lookup that data via a GIN index will be invaluable. I assume even XML storage should become easier as there’s plenty of pre cooked ways to convert XML to JSON.

Let’s create a quick test table:

[postgres]
CREATE TABLE jsonb_test(
id integer PRIMARY KEY,
data jsonb
);
CREATE INDEX jsonb_test_data ON jsonb_test USING gin(data);

— Obviously this data is ridiculous, but we need enough rows for postgres to prefer an index over a seq scan.
INSERT INTO jsonb_test
SELECT i, (‘{"name": "Person’ || i || ‘","age" : ‘ || i || ‘,"address": {"add1": "’
|| i || ‘ Clarence Street","city": "Lancaster","postcode": "LA13BG"}}’)::jsonb
FROM generate_series(1,100000) i;
[/postgres]

Now if we query on the data column we should see the jsonb_test_data index being used:

[postgres]
TEST=# SELECT * FROM jsonb_test
WHERE data @> ‘{"address": {"add1": "2300 Clarence Street"}}’;
id | data
——+—————————————————————————————————————————–
2300 | {"age": 2300, "name": "Person2300", "address": {"add1": "2300 Clarence Street", "city": "Lancaster", "postcode": "LA13BG"}}
(1 row)

Time: 10.811 ms

TEST=# EXPLAIN SELECT * FROM jsonb_test
WHERE data @> ‘{"address": {"add1": "2300 Clarence Street"}}’;
QUERY PLAN
————————————————————————————–
Bitmap Heap Scan on jsonb_test (cost=1040.83..1395.09 rows=107 width=147)
Recheck Cond: (data @> ‘{"address": {"add1": "2300 Clarence Street"}}’::jsonb)
-> Bitmap Index Scan on jsonb_test_data (cost=0.00..1040.80 rows=107 width=0)
Index Cond: (data @> ‘{"address": {"add1": "2300 Clarence Street"}}’::jsonb)
(4 rows)
[/postgres]

Logical Decoding

Whilst Logical Decoding isn’t really in a state to be put into active duty right away, it is pretty special, and allows postgres to supply a stream of changes (or partial changes) in a user defined format. This is similar to what we’ve been doing for ages with trigger based replication like Slony and Londisite, but dissimilar because instead of all the overhead and clunkyness of log triggers the changes are read directly from WAL in a similar way to streaming binary replication. The uses don’t end at master-slave replication either; multimaster and selective replication with per-table granularity, auditing, online upgrades and cache invalidation are just some of the possible uses.

Logical Decoding uses the concept of “replication slots”, which represent a stream of changes logged for a particular consumer, and we can have as many replication slots as we like. The great thing about replication slots is that once they’re created all WAL files required by the slot are retained, and they aren’t just for Logical Decoding; Streaming Replication can make use of them too, so we don’t have to balance wal_keep_segments or rely on archive_command any more. Replication slots aren’t a magic bullet though; if a replication slot isn’t being consumed it will cause postgresql to consume disk space as it retains WAL files for the slot/consumer.

I mentioned earlier that Logical Decoding allows changes to be supplied in a “user defined format”; this is provided by an output plugin in the form of a shared library that needs to be custom written as required, and it’s in this output plugin where the format and any restrictions on what data we want would be controlled. The one exception to this is data used for identifying old rows from updates or deletes, which is defined before it is written to the WAL, and has to be set on a per table basis with ALTER TABLE REPLICA IDENTITY.

There’s a “test_decoding” plugin supplied as a contrib module that we can use for testing, and that’s what I’m going to have a quick look at now.

The first thing we have to do is set wal_level to logical and make sure max_replication_slots is greater than zero. Once we’ve done that and restarted PostgreSQL we’re ready to start playing, and we can create our first replication slot:

[postgres]
TEST=# SELECT * FROM pg_create_logical_replication_slot(‘test_replication_slot’, ‘test_decoding’);
slot_name | xlog_position
———————–+—————
test_replication_slot | 0/56436390
(1 row)
[/postgres]

We should now be able to see our replication slot in the pg_replication_slots view:

[postgres]
TEST=# SELECT * FROM pg_replication_slots;
slot_name | plugin | slot_type | datoid | database | active | xmin | catalog_xmin | restart_lsn
———————–+—————+———–+——–+———-+——–+——+————–+————-
test_replication_slot | test_decoding | logical | 16422 | TEST | f | | 1135904 | 0/56436358
(1 row)
[/postgres]

To look and see if there are any changes, we can use the pg_logical_slot_peek_changes function:

[postgres]
TEST=# \x
Expanded display is on.
TEST=# SELECT * FROM pg_logical_slot_peek_changes(‘test_replication_slot’,NULL, NULL);

-[ RECORD 1 ]——————————————————————————————————————————————————————————————————————————————————————————————————
location | 0/56436450
xid | 1135906
data | BEGIN 1135906
-[ RECORD 2 ]——————————————————————————————————————————————————————————————————————————————————————————————————
location | 0/56436450
xid | 1135906
data | table _test_replication.sl_components: UPDATE: co_actor:’local_sync’ co_pid[integer]:20814 co_node [integer]:0 co_connection_pid[integer]:20831 co_activity:’thread main loop’ co_starttime[timestamp with time zone]:’2014-12-22 16:00:48+00′ co_event[bigint]:null co_eventtype:’n/a’
-[ RECORD 3 ]——————————————————————————————————————————————————————————————————————————————————————————————————
location | 0/56436518
xid | 1135906
data | COMMIT 1135906

< snip >
[/postgres]

… and I’ll snip my output there at 3 rows; I use this machine for Slony testing, so we’re already seeing all of the Slony chatter here, but you should be able to see the capture of an update to the “_test_replication.sl_components” table (this could be any table – I just happened to call my slony cluster “test_replication” too). If you create some activity on your database, you should start so see some output. Notice that the output is the actual changes on the table, not a capture of the sql statement that caused the changes; we can use this change information to build SQL if we want, or some other form DML for another system.

To actually consume the queue we can call pg_logical_slot_get_changes:

[postgres]
TEST=# SELECT * FROM pg_logical_slot_get_changes(‘test_replication_slot’, NULL, NULL);
[/postgres]

This outputs the same as the above, but once we’ve called it the changes are classed as consumed regardless of the caller actually applying them, and will not be output again (nor the WAL reatined). One thing that would be useful here would be the ability to pull the changes, apply them, then confirm them as applied before they’re marked as consumed; I guess this could be achieved by first calling pg_logical_slot_peek_changes, applying the changes and then calling pg_logical_slot_get_changes passing the latest lsn seen from the peek.

In addition to the sql functions, the pg_recvlogical binary is provided to pull data over the streaming replication protocol with something like:

# pg_recvlogical -U postgres -d TEST --slot test_replication_slot --start -f -

For this, as with streaming replication we need to set max_wal_senders greater than zero.

Once we’re finished with our test, we should drop the replication slot:

[postgres]
TEST=# SELECT pg_drop_replication_slot(‘test_replication_slot’);
[/postgres]

Apparently the one thing Logical Decoding can’t do is output DDL, and I’m guessing this is due to other complexities that need to be overcome rather than by design. All exciting!