Tag Archives: postgres

Being cavalier with slony nodes and pg_dump/pg_restore

It’s generally a bad idea to do logical dump/restores of slony nodes, and for this reason slony provides the CLONE PREPARE/CLONE FINISH action commands to clone subscriber nodes.

In this instance though, I’ve a test environment where I’d stopped the slons, dumped out and dropped a subscriber database and then gone on to do some other testing with that postgres cluster. Sometime later I want to do some more testing with the slony cluster; I never dropped this node from the slony config, but in the meantime I’ve changed the postgres version from 9.0 to 9.4 and recreated the postgres cluster with initdb. Schema wise nothing has changed with the old nodes.

What follows is some fudge to make the node resume with replication, it’s neither recommended nor guaranteed to work. Copy this process at your peril.

After recompiling the same version of slony I had before (2.2.4) and installing the binaries, I’ve just restored the old subscriber database dump into the new postgres 9.4 cluster and updated my extensions.

So what’s holding me off just restarting the slons now? Firstly slony stores the oid of each table participating in replication and these will surely have changed now. The following query produces a long list of tables where this is true:

TEST=# SELECT s.tab_set, s.tab_reloid, s.tab_nspname, s.tab_relname, 
	c.oid, n.nspname, c.relname 
FROM _test_replication.sl_table s 
JOIN pg_catalog.pg_class c ON c.oid = s.tab_reloid
JOIN pg_catalog.pg_namespace n ON c.relnamespace = n.oid
WHERE (s.tab_reloid, s.tab_nspname, s.tab_relname) <> (c.oid, n.nspname, c.relname);

The fix here is pretty simple, I could run REPAIR CONFIG against the node, but instead I just hit the updatereloid(<set id>, <node id>) function directly:

TEST=# SELECT s.set_id, s.set_comment,
    CASE _test_replication.updatereloid(s.set_id,1) WHEN 1 THEN 'OK' ELSE 'FAILED' END
FROM _test_replication.sl_set s;

For clarity, my resurrected node is ID 1, and was a subscriber at the time it was destroyed.

Secondly slony stores the transaction ID for each replication event against the node, and if my resurrected node has a lower current xid then new events are going to look like they’re in the past compared to events that have already been generated against the node. I can see the current xid of my new postgresql cluster with the following query:

TEST=# SELECT txid_current();
 txid_current
--------------
        25765

And I can compare this to slony events generated against the node in its old incarnation as follows:

TEST=# SELECT max(txid_snapshot_xmax(ev_snapshot)), txid_current(), txid_current()-max(txid_snapshot_xmax(ev_snapshot)) AS delta
FROM _test_replication.sl_event where ev_origin = 1;

  max  | txid_current | delta
-------+--------------+--------
 89004 |        25767 | -63237

So transaction ID wise my node is in the past, to bump that up I need about 63237 transactions to happen, if that were a lot higher I’d have to think of another way (perhaps by stopping all the slons and updating all values of ev_snapshot for node 1 on all nodes), but I can easily generate 60k transactions by hitting txid_current():

$ while [ 1 ]; do psql -U glyn -d TEST -tAc "SELECT txid_current();"; done
25768
25769
25770

<snip>

89002
89003
89004
89005
89006
^C
$ 

I can now restart my slons and replication should continue, and so far all appears well.

Wanting hstore style operators in jsonb – revisited

A couple of weeks ago I wrote about wanting a jsonb delete operator in 9.4, and yesterday evening I decided to have a go at writing some functions in C.

In the end all I actually did yesterday was make a mess and read a lot of existing code, but persisting this evening I’ve managed to put together some functions that appear to work. I’m not confident to say they’re efficient (or even correct; and they certainly shouldn’t be put on production systems), but I thought it’d be useful to benchmark them.

I’ve also added in a concatenate operator after reading Matthew Schinckel’s post.

First install the C shared library:

# make install 

Then install the functions and operators, these functions are named jsonb_delete and jsonb_concat:

test=# \i jsonb_opx.sql
CREATE FUNCTION
COMMENT
CREATE OPERATOR
COMMENT
CREATE FUNCTION
COMMENT
CREATE OPERATOR
COMMENT
CREATE FUNCTION
COMMENT
CREATE OPERATOR
COMMENT
CREATE FUNCTION
COMMENT
CREATE OPERATOR
COMMENT

Then install the SQL versions for comparison, these functions are named jsonb_delete_left and jsonb_concat_left:

test=# \i jsonb_opx_sql_comparison.sql
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION

Test 1 – deleteing a key

This is actually an SQL wrapper to the C function for (jsonb, text[]), breaking that up
to have a separate version would be more efficient, but that should be a trivial task.

test=# \timing on
Timing is on.
test=# SELECT '{"a": 1, "b": 2, "c": 3}'::jsonb - 'b'::text;
     ?column?     
------------------
 {"a": 1, "c": 3}
(1 row)

Time: 7.099 ms

The above is hitting the C function; from this point onwards I’ll just hit the functions directly:

test=# SELECT jsonb_delete('{"a": 1, "b": 2, "c": 3}'::jsonb, 'b');
   jsonb_delete   
------------------
 {"a": 1, "c": 3}
(1 row)
Time: 6.220 ms

Now the original SQL version:

test=# SELECT jsonb_delete_left('{"a": 1, "b": 2, "c": 3}'::jsonb, 'b');
 jsonb_delete_left 
-------------------
 {"a": 1, "c": 3}
(1 row)

Time: 14.570 ms

Now to benchmark for a large quantity of rows:

test=# EXPLAIN ANALYZE SELECT jsonb_delete(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb, 'b')
FROM generate_series(1,10000) x;
                                                         QUERY PLAN                                                         
----------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..300.00 rows=1000 width=4) (actual time=10.407..263.489 rows=10000 loops=1)
 Planning time: 0.335 ms
 Execution time: 290.192 ms
(3 rows)

Time: 293.254 ms
test=# EXPLAIN ANALYZE SELECT jsonb_delete_left(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb, 'b')
FROM generate_series(1,10000) x;
                                                         QUERY PLAN                                                         
----------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..300.00 rows=1000 width=4) (actual time=15.165..767.706 rows=10000 loops=1)
 Planning time: 0.785 ms
 Execution time: 803.258 ms
(3 rows)

Time: 809.088 ms

Whilst processing 1 row really doesn’t show any improvement (the timings for both varied in the 2~10ms range), with 10,000 rows the C version is just over twice as quick.

If these times stick out as particularly dire, it’s probably just because the machine I’m testing on is very old.

Test 2 – deleting multiple keys

test=# SELECT jsonb_delete('{"a": 1, "b": 2, "c": 3}'::jsonb, ARRAY['a','b']);
 jsonb_delete 
--------------
 {"c": 3}
(1 row)

Time: 3.482 ms

test=# SELECT jsonb_delete_left('{"a": 1, "b": 2, "c": 3}'::jsonb, ARRAY['a','b']);
 jsonb_delete_left 
-------------------
 {"c": 3}
(1 row)

Time: 3.613 ms
test=# EXPLAIN ANALYZE SELECT jsonb_delete(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb, ARRAY['a','b'])
FROM generate_series(1,10000) x;
                                                        QUERY PLAN                                                        
--------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..52.50 rows=1000 width=4) (actual time=5.805..177.507 rows=10000 loops=1)
 Planning time: 1.646 ms
 Execution time: 209.137 ms
(3 rows)

Time: 213.507 ms

test=# EXPLAIN ANALYZE SELECT jsonb_delete_left(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb, ARRAY['a','b'])
FROM generate_series(1,10000) x;
                                                         QUERY PLAN                                                         
----------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..300.00 rows=1000 width=4) (actual time=15.805..757.500 rows=10000 loops=1)
 Planning time: 0.595 ms
 Execution time: 789.272 ms
(3 rows)

Time: 793.229 ms

Results are similar; we’re essentially hitting the same C function.

Test 3 – Deleting matching jsonb key/value pairs

The C version of this function essentially loops round the left jsonb value looking up keys
in the right jsonb value. If it finds a matching key it does a string based comparison on
the values (treating nested jsonb as a string too) and if the values match as well then the key/value pair is removed.

test=# SELECT jsonb_delete('{"a": 1, "b": 2, "c": 3}'::jsonb, '{"a": 4, "b": 2}'::jsonb);
   jsonb_delete   
------------------
 {"a": 1, "c": 3}
(1 row)

Time: 3.114 ms
test=# SELECT jsonb_delete_left('{"a": 1, "b": 2, "c": 3}'::jsonb, '{"a": 4, "b": 2}'::jsonb);
 jsonb_delete_left 
-------------------
 {"a": 1, "c": 3}
(1 row)

Time: 6.899 ms
test=# EXPLAIN ANALYZE SELECT jsonb_delete(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb,
('{"a":' || x || ', "d":' || x*2 || ', "c":' || x*10 || '}')::jsonb)
FROM generate_series(1,10000) x;
                                                        QUERY PLAN                                                        
--------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..92.50 rows=1000 width=4) (actual time=8.452..238.210 rows=10000 loops=1)
 Planning time: 0.428 ms
 Execution time: 266.358 ms
(3 rows)

Time: 270.161 ms

test=# EXPLAIN ANALYZE SELECT jsonb_delete_left(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb,
('{"a":' || x || ', "d":' || x*2 || ', "c":' || x*10 || '}')::jsonb)
FROM generate_series(1,10000) x;
                                                         QUERY PLAN                                                          
-----------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..340.00 rows=1000 width=4) (actual time=11.833..1206.990 rows=10000 loops=1)
 Planning time: 0.759 ms
 Execution time: 1248.481 ms
(3 rows)

Time: 1253.392 ms

There’s a bigger improvement here; it’s about 4.5 times quicker.

Test 4 – concatenation

The C function for this is essentially a cut n shut job on both jsonb values, blindly
pushing all the values onto the return value and leaving the lower level jsonb api
to do the deduplication:

test=# SELECT jsonb_concat('{"a": 1, "b": 2, "c": 3}'::jsonb, '{"a": 4, "d": 4, "z": 26}'::jsonb);
               jsonb_concat                
-------------------------------------------
 {"a": 4, "b": 2, "c": 3, "d": 4, "z": 26}
(1 row)

Time: 3.028 ms

test=# SELECT jsonb_concat_left('{"a": 1, "b": 2, "c": 3}'::jsonb, '{"a": 4, "d": 4, "z": 26}'::jsonb);
             jsonb_concat_left             
-------------------------------------------
 {"a": 4, "b": 2, "c": 3, "d": 4, "z": 26}
(1 row)

Time: 4.731 ms

Again nothing to get excited about. Testing on a larger quantity of rows shows a similar improvement to the jsonb -jsonb delete operator/function above:

test=# EXPLAIN ANALYZE SELECT jsonb_concat(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb,
('{"a":' || x || ', "d":' || x*2 || ', "c":' || x*10 || '}')::jsonb)
FROM generate_series(1,10000) x;
                                                        QUERY PLAN                                                         
---------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..92.50 rows=1000 width=4) (actual time=12.481..255.910 rows=10000 loops=1)
 Planning time: 0.599 ms
 Execution time: 285.357 ms
(3 rows)

Time: 288.615 ms

test=# EXPLAIN ANALYZE SELECT jsonb_concat_left(('{"a":' || x || ', "b":' || x*2 || ', "c":' || x*x || '}')::jsonb,
('{"a":' || x || ', "d":' || x*2 || ', "c":' || x*10 || '}')::jsonb)
FROM generate_series(1,10000) x;
                                                         QUERY PLAN                                                          
-----------------------------------------------------------------------------------------------------------------------------
 Function Scan on generate_series x  (cost=0.00..340.00 rows=1000 width=4) (actual time=13.931..1051.100 rows=10000 loops=1)
 Planning time: 5.160 ms
 Execution time: 1091.596 ms
(3 rows)

Time: 1103.165 ms

So in conclusion the results are nothing earth shattering, but there is a small improvement. Essentially all these functions are doing is iterating around the jsonb and building new return values; it’d be nice to see what someone more familiar with the jsonb internals at a lower level could come up with.

Wanting for a hstore style delete operator in jsonb

PostgreSQL 9.4 intorduced the jsonb type, but it’d be nice to be able to delete keys and pairs using the “-” operator; just like you can with the hstore type.

Fortunately postgres makes creating an operator really easy for us, so lets have a go at creating a delete operator for jsonb.

First lets try to create an operator just to delete one key passed as text. We need to start by creating a function for our operator, and the only way I can think to do this looking at the docs is to unwrap the json with jsonb_each, filter out the matches, and roll it all back up:

TEST=# CREATE OR REPLACE FUNCTION jsonb_delete_left(a jsonb, b text)
       RETURNS jsonb AS
       $BODY$
       SELECT COALESCE(
              (
              SELECT ('{' || string_agg(to_json(key) || ':' || value, ',') || '}')
              FROM jsonb_each(a)
              WHERE key <> b
              )
       , '{}')::jsonb;
       $BODY$
       LANGUAGE sql IMMUTABLE STRICT;
CREATE FUNCTION

TEST=# COMMENT ON FUNCTION jsonb_delete_left(jsonb, text) IS 'delete key in second argument from first argument';
COMMENT

Once we’ve created our function, we just need to create the operator to use it:

TEST=# CREATE OPERATOR - ( PROCEDURE = jsonb_delete_left, LEFTARG = jsonb, RIGHTARG = text);
CREATE OPERATOR
TEST=# COMMENT ON OPERATOR - (jsonb, text) IS 'delete key from left operand';
COMMENT

And we’re ready to go:

TEST=# SELECT '{"a": 1, "b": 2, "c": 3}'::jsonb - 'b'::text;
     ?column?     
------------------
 {"a": 1, "c": 3}
(1 row)

Seems to work, lets now try to create one that will let us delete a set of keys passed as an array:

TEST=# CREATE OR REPLACE FUNCTION jsonb_delete_left(a jsonb, b text[])
       RETURNS jsonb AS
       $BODY$
       SELECT COALESCE(
              (
              SELECT ('{' || string_agg(to_json(key) || ':' || value, ',') || '}')
              FROM jsonb_each(a)
              WHERE key <> ALL(b)
              )
       , '{}')::jsonb;
       $BODY$
       LANGUAGE sql IMMUTABLE STRICT;
CREATE FUNCTION

TEST=# COMMENT ON FUNCTION jsonb_delete_left(jsonb, text[]) IS 'delete keys in second argument from first argument';
COMMENT

TEST=# CREATE OPERATOR - ( PROCEDURE = jsonb_delete_left, LEFTARG = jsonb, RIGHTARG = text[]);
CREATE OPERATOR

TEST=# COMMENT ON OPERATOR - (jsonb, text[]) IS 'delete keys from left operand';
COMMENT

TEST=# SELECT '{"a": 1, "b": 2, "c": 3}'::jsonb - ARRAY['a','b'];
 ?column? 
----------
 {"c": 3}
(1 row)

Ok, so now lets create one to delete matching key/value pairs:

TEST=# CREATE OR REPLACE FUNCTION jsonb_delete_left(a jsonb, b jsonb)
       RETURNS jsonb AS
       $BODY$
       SELECT COALESCE(
              (
              SELECT ('{' || string_agg(to_json(key) || ':' || value, ',') || '}')
              FROM jsonb_each(a)
              WHERE NOT ('{' || to_json(key) || ':' || value || '}')::jsonb <@ b
              )
       , '{}')::jsonb;
       $BODY$
       LANGUAGE sql IMMUTABLE STRICT;
CREATE FUNCTION

TEST=# COMMENT ON FUNCTION jsonb_delete_left(jsonb, jsonb) IS 'delete matching pairs in second argument from first argument';
COMMENT

TEST=# CREATE OPERATOR - ( PROCEDURE = jsonb_delete_left, LEFTARG = jsonb, RIGHTARG = jsonb);
CREATE OPERATOR

TEST=# COMMENT ON OPERATOR - (jsonb, jsonb) IS 'delete matching pairs from left operand';
COMMENT

TEST=# SELECT '{"a": 1, "b": 2, "c": 3}'::jsonb - '{"a": 4, "b": 2}'::jsonb;
     ?column?     
------------------
 {"a": 1, "c": 3}
(1 row)

Seems to work fine to me, lets try an index:

TEST=# \timing on
Timing is on
TEST=# CREATE TABLE jsonb_test (a jsonb, b jsonb);
CREATE TABLE
Time: 207.038 ms

TEST=# INSERT INTO jsonb_test VALUES ('{"a": 1, "b": 2, "c": 3}', '{"a": 4, "b": 2}');
INSERT 0 1
Time: 39.979 ms

TEST=# SELECT * FROM jsonb_test WHERE a-b = '{"a": 1, "c": 3}'::jsonb;
            a             |        b         
--------------------------+------------------
 {"a": 1, "b": 2, "c": 3} | {"a": 4, "b": 2}
(1 row)

Time: 47.197 ms

TEST=# INSERT INTO jsonb_test
       SELECT ('{"a" : ' || i+1 || ',"b" : ' || i+2 || ',"c": ' || i+3 || '}')::jsonb,
       ('{"a" : ' || i+2 || ',"b" : ' || i || ',"c": ' || i+5 || '}')::jsonb
       FROM generate_series(1,1000) i;
INSERT 0 1000
Time: 84.765 ms

TEST=# CREATE INDEX ON jsonb_test USING gin((a-b));
CREATE INDEX
Time: 229.050 ms
TEST=# EXPLAIN SELECT * FROM jsonb_test WHERE a-b @> '{"a": 1, "c": 3}';
                                    QUERY PLAN                                     
-----------------------------------------------------------------------------------
 Bitmap Heap Scan on jsonb_test  (cost=20.26..24.52 rows=1 width=113)
   Recheck Cond: ((a - b) @> '{"a": 1, "c": 3}'::jsonb)
   ->  Bitmap Index Scan on jsonb_test_expr_idx  (cost=0.00..20.26 rows=1 width=0)
         Index Cond: ((a - b) @> '{"a": 1, "c": 3}'::jsonb)
(4 rows)

Time: 13.277 ms

All seems to work as expected. I guess the one thing I’m not so certain about here is if any of this behaves correctly once we start getting nested json, but at first glance it doesn’t look too wonky to me:

TEST=# SELECT '{"a": 1, "b": 2, "c": 3, "d": {"a": 4}}'::jsonb - '{"d": {"a": 4}, "b": 2}'::jsonb;
     ?column?     
------------------
 {"a": 1, "c": 3}

TEST=# SELECT '{"a": 4, "b": 2, "c": 3, "d": {"a": 4}}'::jsonb - '{"a": 4, "b": 2}'::jsonb;
        ?column?         
-------------------------
 {"c": 3, "d": {"a": 4}}
(1 row

Of course being written in sql these probably aren’t anywhere near as fast as the hstore equivalents which are written in C, so it’d be nice to see something in core postgres to do this.