imay commented on a change in pull request #832: Support hll_raw_agg in
Aggregate Function
URL: https://github.com/apache/incubator-doris/pull/832#discussion_r270696881
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File path: docs/help/Contents/Data Definition/ddl_stmt.md
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@@ -952,38 +955,40 @@
b. 使用数据中的某一列生成hll列
curl --location-trusted -uname:password -T data
http://host/api/test_db/test/_load?label=load_1\&hll=set1,cuid:set2,os
- \&columns=time,id,name,province,sex,cuid,os
+ \&columns=dt,id,name,province,sex,cuid,os
3. 聚合数据，常用方式3种：（如果不聚合直接对base表查询，速度可能跟直接使用ndv速度差不多）
a. 创建一个rollup，让hll列产生聚合，
- alter table test add rollup test_rollup(date, set1);
+ alter table test add rollup test_rollup(dt, set1);
b. 创建另外一张专门计算uv的表，然后insert数据）
create table test_uv(
- time date,
+ dt date,
uv_set hll hll_union)
distributed by hash(id) buckets 32;
- insert into test_uv select date, set1 from test;
+ insert into test_uv select dt, set1 from test;
c. 创建另外一张专门计算uv的表，然后insert并通过hll_hash根据test其它非hll列生成hll列
create table test_uv(
- time date,
+ dt date,
id_set hll hll_union)
distributed by hash(id) buckets 32;
- insert into test_uv select date, hll_hash(id) from test;
+ insert into test_uv select dt, hll_hash(id) from test;
4. 查询，hll列不允许直接查询它的原始值，可以通过配套的函数进行查询
a. 求总uv
select HLL_UNION_AGG(uv_set) from test_uv;
b. 求每一天的uv
- select HLL_CARDINALITY(uv_set) from test_uv;
+ select dt, HLL_CARDINALITY(uv_set) from test_uv;
+ select dt, HLL_CARDINALITY(uv) from (select dt, HLL_RAW_AGG(set1) as
uv from test group by dt) tmp;
+ select dt, HLL_UNION_AGG(set1) as uv from test group by dt;
Review comment:
I think that these three queries don't lead to same result.
1 would return many rows for one `dt` value
2 and 3 queries would group by `dt` column and return one row for each value
So, you should split them into different examples
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