In this study, I wanted to see what performance improvements can be obtained using a ClickHouse data source rather than PostgreSQL. I know what performance benefits I get when using ClickHouse. Will these benefits persist if I access ClickHouse from PostgreSQL using an external data wrapper (FDW)?
The studied database environments are PostgreSQL v11, clickhousedb_fdw, and ClickHouse database. Ultimately, from PostgreSQL v11, we will run various SQL queries routed through our clickhousedb_fdw to the ClickHouse database. We will then see how the performance of FDW compares to the same queries executed in native PostgreSQL and native ClickHouse.
Clickhouse database
ClickHouse is an open source column-based database management system that can achieve performance 100-1000 times faster than traditional database approaches, capable of handling over a billion rows in less than a second.
Clickhousedb_fdw
clickhousedb_fdw - ClickHouse External Database Wrapper, or FDW, is an open source project from Percona. Here is a link to the project's GitHub repository .
In March, I wrote a blog that tells you more about our FDW .
As you will see, this provides FDW for ClickHouse, which allows SELECT from, and INSERT INTO, a ClickHouse database from PostgreSQL v11 server.
FDW , aggregate join. .
Benchmark environment
- Supermicro server:
- Intel® Xeon® CPU E5-2683 v3 @ 2.00GHz
- 2 sockets / 28 cores / 56 threads
- Memory: 256GB of RAM
- Storage: Samsung SM863 1.9TB Enterprise SSD
- Filesystem: ext4/xfs
- OS: Linux smblade01 4.15.0-42-generic #45~16.04.1-Ubuntu
- PostgreSQL: version 11
Benchmark tests
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Benchmark Queries
, ClickHouse, clickhousedb_fdw PostgreSQL.
| Q# | Query Contains Aggregates and Group By |
|---|---|
| Q1 | SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY DayOfWeek ORDER BY c DESC; |
| Q2 | SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year >= 2000 AND Year <= 2008 GROUP BY DayOfWeek ORDER BY c DESC; |
| Q3 | SELECT Origin, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year >= 2000 AND Year <= 2008 GROUP BY Origin ORDER BY c DESC LIMIT 10; |
| Q4 | SELECT Carrier, count() FROM ontime WHERE DepDelay>10 AND Year = 2007 GROUP BY Carrier ORDER BY count() DESC; |
| Q5 | SELECT a.Carrier, c, c2, c1000/c2 as c3 FROM ( SELECT Carrier, count() AS c FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier ) a INNER JOIN ( SELECT Carrier,count(*) AS c2 FROM ontime WHERE Year=2007 GROUP BY Carrier)b on a.Carrier=b.Carrier ORDER BY c3 DESC; |
| Q6 | SELECT a.Carrier, c, c2, c1000/c2 as c3 FROM ( SELECT Carrier, count() AS c FROM ontime WHERE DepDelay>10 AND Year >= 2000 AND Year <= 2008 GROUP BY Carrier) a INNER JOIN ( SELECT Carrier, count(*) AS c2 FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY Carrier ) b on a.Carrier=b.Carrier ORDER BY c3 DESC; |
| Q7 | SELECT Carrier, avg(DepDelay) * 1000 AS c3 FROM ontime WHERE Year >= 2000 AND Year <= 2008 GROUP BY Carrier; |
| Q8 | SELECT Year, avg(DepDelay) FROM ontime GROUP BY Year; |
| Q9 | select Year, count(*) as c1 from ontime group by Year; |
| Q10 | SELECT avg(cnt) FROM (SELECT Year,Month,count(*) AS cnt FROM ontime WHERE DepDel15=1 GROUP BY Year,Month) a; |
| Q11 | select avg(c1) from (select Year,Month,count(*) as c1 from ontime group by Year,Month) a; |
| Q12 | SELECT OriginCityName, DestCityName, count(*) AS c FROM ontime GROUP BY OriginCityName, DestCityName ORDER BY c DESC LIMIT 10; |
| Q13 | SELECT OriginCityName, count(*) AS c FROM ontime GROUP BY OriginCityName ORDER BY c DESC LIMIT 10; |
| Query Contains Joins | |
| Q14 | SELECT a.Year, c1/c2 FROM ( select Year, count()1000 as c1 from ontime WHERE DepDelay>10 GROUP BY Year) a INNER JOIN (select Year, count(*) as c2 from ontime GROUP BY Year ) b on a.Year=b.Year ORDER BY a.Year; |
| Q15 | SELECT a.”Year”, c1/c2 FROM ( select “Year”, count()1000 as c1 FROM fontime WHERE “DepDelay”>10 GROUP BY “Year”) a INNER JOIN (select “Year”, count(*) as c2 FROM fontime GROUP BY “Year” ) b on a.”Year”=b.”Year”; |
Table-1: Queries used in benchmark
Query executions
: PostgreSQL , ClickHouse clickhousedb_fdw. .
| Q# | PostgreSQL | PostgreSQL (Indexed) | ClickHouse | clickhousedb_fdw |
|---|---|---|---|---|
| Q1 | 27920 | 19634 | 23 | 57 |
| Q2 | 35124 | 17301 | 50 | 80 |
| Q3 | 34046 | 15618 | 67 | 115 |
| Q4 | 31632 | 7667 | 25 | 37 |
| Q5 | 47220 | 8976 | 27 | 60 |
| Q6 | 58233 | 24368 | 55 | 153 |
| Q7 | 30566 | 13256 | 52 | 91 |
| Q8 | 38309 | 60511 | 112 | 179 |
| Q9 | 20674 | 37979 | 31 | 81 |
| Q10 | 34990 | 20102 | 56 | 148 |
| Q11 | 30489 | 51658 | 37 | 155 |
| Q12 | 39357 | 33742 | 186 | 1333 |
| Q13 | 29912 | 30709 | 101 | 384 |
| Q14 | 54126 | 39913 | 124 | 1364212 |
| Q15 | 97258 | 30211 | 245 | 259 |
Table-1: Time taken to execute the queries used in benchmark
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ClickhouseDB clickhousedb_fdw. FDW , Q12. ORDER BY. - ORDER BY GROUP/BY ORDER BY ClickHouse.
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Q15: Without ORDER BY Clause
bm=# EXPLAIN VERBOSE SELECT a."Year", c1/c2
FROM (SELECT "Year", count(*)*1000 AS c1 FROM fontime WHERE "DepDelay" > 10 GROUP BY "Year") a
INNER JOIN(SELECT "Year", count(*) AS c2 FROM fontime GROUP BY "Year") b ON a."Year"=b."Year";Q15: Query Without ORDER BY Clause
QUERY PLAN
Hash Join (cost=2250.00..128516.06 rows=50000000 width=12)
Output: fontime."Year", (((count(*) * 1000)) / b.c2)
Inner Unique: true Hash Cond: (fontime."Year" = b."Year")
-> Foreign Scan (cost=1.00..-1.00 rows=100000 width=12)
Output: fontime."Year", ((count(*) * 1000))
Relations: Aggregate on (fontime)
Remote SQL: SELECT "Year", (count(*) * 1000) FROM "default".ontime WHERE (("DepDelay" > 10)) GROUP BY "Year"
-> Hash (cost=999.00..999.00 rows=100000 width=12)
Output: b.c2, b."Year"
-> Subquery Scan on b (cost=1.00..999.00 rows=100000 width=12)
Output: b.c2, b."Year"
-> Foreign Scan (cost=1.00..-1.00 rows=100000 width=12)
Output: fontime_1."Year", (count(*))
Relations: Aggregate on (fontime)
Remote SQL: SELECT "Year", count(*) FROM "default".ontime GROUP BY "Year"(16 rows)Q14: Query With ORDER BY Clause
bm=# EXPLAIN VERBOSE SELECT a."Year", c1/c2 FROM(SELECT "Year", count(*)*1000 AS c1 FROM fontime WHERE "DepDelay" > 10 GROUP BY "Year") a
INNER JOIN(SELECT "Year", count(*) as c2 FROM fontime GROUP BY "Year") b ON a."Year"= b."Year"
ORDER BY a."Year";Q14: Query Plan with ORDER BY Clause
QUERY PLAN
Merge Join (cost=2.00..628498.02 rows=50000000 width=12)
Output: fontime."Year", (((count(*) * 1000)) / (count(*)))
Inner Unique: true Merge Cond: (fontime."Year" = fontime_1."Year")
-> GroupAggregate (cost=1.00..499.01 rows=1 width=12)
Output: fontime."Year", (count(*) * 1000)
Group Key: fontime."Year"
-> Foreign Scan on public.fontime (cost=1.00..-1.00 rows=100000 width=4)
Remote SQL: SELECT "Year" FROM "default".ontime WHERE (("DepDelay" > 10))
ORDER BY "Year" ASC
-> GroupAggregate (cost=1.00..499.01 rows=1 width=12)
Output: fontime_1."Year", count(*) Group Key: fontime_1."Year"
-> Foreign Scan on public.fontime fontime_1 (cost=1.00..-1.00 rows=100000 width=4)
Remote SQL: SELECT "Year" FROM "default".ontime ORDER BY "Year" ASC(16 rows), ClickHouse , clickhousedb_fdw ClickHouse PostgreSQL. clickhousedb_fdw , , ClickHouse. , fdw PostgreSQL .
Clickhouse https://t.me/clickhouse_ru
PostgreSQL https://t.me/pgsql