On Mar 11, 2016 4:40 PM, "Paul Jones" <pbj@xxxxxxxxxx> wrote:
>
> I have been running the EDB benchmark that compares Postgres and MongoDB.
> I believe EDB ran it against PG 9.4 and Mongo 2.6. I am running it
> against PG 9.5.1 and Mongo 3.2 with WiredTiger storage using 10,000,000
> JSON records generated by the benchmark. It looks like Mongo is winning,
> and apparently because of its cache management.
Dmitry was working on the same benchmarks. I think edb benchmark is broken by design. Better, use ycsb benchmarks. I hope, Dmitry will share his
results.
>
> The first queries on both run in ~30 min. And, once PG fills its cache,
> it whips Mongo on repeats of the *same* query (vmstat shows no disk
> reads for PG).
>
> However, when different query on the same table is issued to both,
> vmstat shows that PG has to read the *entire* table again, and it takes
> ~30 min. Mongo does a lot of reads initially but after about 5 minutes,
> it stops reading and completes the query, most likely because it is
> using its cache very effectively.
>
> Host: Virtual Machine
> 4 CPUs
> 16 Gb RAM
> 200 Gb Disk
> RHEL 6.6
>
> PG: 9.5.1 compiled from source
> shared_buffers = 7GB
> effectve_cache_size = 12GB
>
> Mongo: 3.2 installed with RPM from Mongo
>
> In PG, I created the table by:
>
> CREATE TABLE json_tables
> (
> data JSONB
> );
>
> After loading, it creates the index:
>
> CREATE INDEX json_tables_idx ON json_tables USING GIN (data jsonb_path_ops);
>
> After a lot of experimentation, I discovered that the benchmark was not
> using PG's index, so I modified the four queries to be:
>
> SELECT data FROM json_tables WHERE data @> '{"brand": "ACME"}';
> SELECT data FROM json_tables WHERE data @> '{"name": "Phone Service Basic Plan"}';
> SELECT data FROM json_tables WHERE data @> '{"name": "AC3 Case Red"}';
> SELECT data FROM json_tables WHERE data @> '{"type": "service"}';
>
> Here are two consecutive explain analyze for PG, for the same query.
> No functional difference in the plans that I can tell, but the effect
> of PG's cache on the second is dramatic.
>
> If anyone has ideas on how I can get PG to more effectively use the cache
> for subsequent queries, I would love to hear them.
>
> -------
>
> benchmark=# explain analyze select data from json_tables where data @> '{"name": "AC3 Case Red"}';
>
> QUERY PLAN
>
>
> -----------------------------------------------------------------------------------------------------------------------------------------
>
> Bitmap Heap Scan on json_tables (cost=113.50..37914.64 rows=10000 width=1261)
> (actual time=2157.118..1259550.327 rows=909091 loops=1)
> Recheck Cond: (data @> '{"name": "AC3 Case Red"}'::jsonb)
> Rows Removed by Index Recheck: 4360296
> Heap Blocks: exact=37031 lossy=872059
> -> Bitmap Index Scan on json_tables_idx (cost=0.00..111.00 rows=10000 width =0) (actual time=2141.250..2141.250 rows=909091 loops=1)
> Index Cond: (data @> '{"name": "AC3 Case Red"}'::jsonb)
> Planning time: 291.932 ms
> Execution time: 1259886.920 ms
> (8 rows)
>
> Time: 1261191.844 ms
>
> benchmark=# explain analyze select data from json_tables where data @> '{"name": "AC3 Case Red"}';
> QUERY PLAN
>
> ---------------------------------------------------------------------------------------------------------------------------------------
>
> Bitmap Heap Scan on json_tables (cost=113.50..37914.64 rows=10000 width=1261) (actual time=779.261..29815.262 rows=909091 loops=1)
> Recheck Cond: (data @> '{"name": "AC3 Case Red"}'::jsonb)
> Rows Removed by Index Recheck: 4360296
> Heap Blocks: exact=37031 lossy=872059
> -> Bitmap Index Scan on json_tables_idx (cost=0.00..111.00 rows=10000 width =0) (actual time=769.081..769.081 rows=909091 loops=1)
> Index Cond: (data @> '{"name": "AC3 Case Red"}'::jsonb)
> Planning time: 33.967 ms
> Execution time: 29869.381 ms
>
> (8 rows)
>
> Time: 29987.122 ms
>
>
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