在本研究中，我想看看使用ClickHouse数据源而不是PostgreSQL可以获得哪些性能改进。我知道使用ClickHouse可以获得什么性能上的好处。如果我使用外部数据包装程序（FDW）从PostgreSQL访问ClickHouse，这些好处是否还会持续存在？
研究的数据库环境是PostgreSQL v11，clickhousedb_fdw和ClickHouse数据库。最终，从PostgreSQL v11开始，我们将运行通过clickhousedb_fdw路由到ClickHouse数据库的各种SQL查询。然后，我们将看到FDW的性能与本机PostgreSQL和本机ClickHouse中执行的相同查询相比。
Clickhouse数据库
ClickHouse是一种基于列的开源数据库管理系统，其性能比传统数据库方法快100-1000倍，能够在不到一秒钟的时间内处理十亿行。
Clickhousedb_fdw
clickhousedb_fdw-ClickHouse外部数据库包装程序或FDW是Percona的开源项目。这是项目的GitHub存储库的链接。
如您将看到的，这为ClickHouse提供了FDW，它允许SELECT从PostgreSQL v11服务器中进行选择，并从INSERT INTO到ClickHouse数据库。
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.
2 Q12 Q13. , ORDER BY. , Q-14 Q-15 ORDER BY . ORDER BY 259 , ORDER BY — 1364212. , .
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