为什么 Clickhouse 比 PostgreSQL 慢？

Question

我想将 Clickhouse 用作 OLAP，将 PostgreSQL 用作 OLTP 数据库。

问题是查询 Clickhouse 运行比在 Postgres 上慢。查询如下：

select count(id) from {table_name}

这是我的 table 结构：

CREATE TABLE IF NOT EXISTS {table_name} 
        (
            `id` UInt64,
            `label` Nullable(FixedString(50)),
            `query` Nullable(text),
            `creation_datetime` DateTime,
            `offset` UInt64,
            `user_is_first_search` UInt8,
            `user_date_of_start` Date,
            `usage_type` Nullable(FixedString(20)),
            `user_ip` Nullable(FixedString(200)),
            `who_searched_query` Nullable(FixedString(15)),
            `device_type` Nullable(FixedString(20)),
            `device_os` Nullable(FixedString(20)),
            `tab_type` Nullable(FixedString(20)),
            `response_api_type` Nullable(FixedString(20)),
            `total_response_time` Float64,
            `retrieved_instant_answer` Nullable(FixedString(100)),
            `is_relative_instant_answer` UInt8,
            `meta_search_instant_answer_type` Nullable(FixedString(50)),
            `settings_alignment` Nullable(FixedString(20)),
            `settings_safe_search` Nullable(FixedString(30)),
            `settings_search_results_number` Nullable(FixedString(30)),
            `settings_proxy_image_urls` Nullable(FixedString(30)),
            `cache_hit` Nullable(FixedString(20)),
            `net_status` Nullable(FixedString(20)),
            `is_transitional` UInt8
        )
        ENGINE = MergeTree() PARTITION BY creation_datetime ORDER BY (id)

我在两个数据库中的日期时间字段上创建了一个索引，然后运行 optimize 对两个数据库都进行了查询。谁能告诉我为什么 Clickhouse 比 Postgres 慢？

Answer 1

Clickhouse 有很多方法可以让你大吃一惊

create table test ( id Int64, d Date ) Engine=MergeTree Order by id;
insert into test select number, today() from numbers(1e9);

select count() from test;
┌───count()─┐
│ 100000000 │
└───────────┘
1 rows in set. Elapsed: 0.002 sec.

select count(id) from test;
┌─count(id)─┐
│ 100000000 │
└───────────┘
1 rows in set. Elapsed: 0.239 sec. Processed 100.00 million rows, 800.00 MB (418.46 million rows/s., 3.35 GB/s.)


drop table test;

create table test ( id Int64, d Int64 ) Engine=MergeTree partition by (intDiv(d, 10000)) Order by id;
set max_partitions_per_insert_block=0;
insert into test select number, number from numbers(1e8);

select count(id) from test;
┌─count(id)─┐
│ 100000000 │
└───────────┘
1 rows in set. Elapsed: 1.050 sec. Processed 100.00 million rows, 800.00 MB (95.20 million rows/s., 761.61 MB/s.)


select count(d) from test;
┌──count(d)─┐
│ 100000000 │
└───────────┘
1 rows in set. Elapsed: 0.004 sec.

Answer 2

终于找到我做错的地方了。我不应该按日期时间字段进行分区。我创建了没有分区的 table，它变得非常快。

为什么 Clickhouse 比 PostgreSQL 慢？

Why is Clickhouse slower than PostgreSQL?

postgresql

olap

clickhouse