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Clickhouse example AggregatingMergeTree, (max, min, avg ) State / Merge
DROP TABLE IF EXISTS requests;
CREATE TABLE requests (
request_date Date,
request_time DateTime,
response_time Int,
request_uri String)
ENGINE = MergeTree(request_date, (request_time, request_uri), 8192);
DROP TABLE IF EXISTS requests_graph;
CREATE MATERIALIZED VIEW requests_graph
ENGINE = AggregatingMergeTree(request_date, (request_hour,request_uri), 8192)
AS SELECT
request_date,
toStartOfHour(request_time) request_hour,
request_uri,
avgState(response_time) avg_response_time,
maxState(response_time) max_response_time,
minState(response_time) min_response_time,
countState() request_count
FROM requests
GROUP BY request_date, request_hour, request_uri;
insert into requests values (today(), now(), 10, 'ya.ru');
insert into requests values (today(), now(), 20, 'ya.ru');
insert into requests values (today(), now(), 10, 'google.ru');
insert into requests values (today(), now()+7200, 20, 'google.ru');
SELECT request_date,
request_hour,
request_uri,
avgMerge(avg_response_time) avg_response_time,
maxMerge(max_response_time) max_response_time,
minMerge(min_response_time) min_response_time,
countMerge(request_count) request_cnt
FROM requests_graph
GROUP BY request_date, request_hour, request_uri;
┌─request_date─┬────────request_hour─┬─request_uri─┬─avg_response_time─┬─max_response_time─┬─min_response_time─┬─request_cnt─┐
│ 2018-03-31 │ 2018-03-31 03:00:00 │ ya.ru │ 15 │ 20 │ 10 │ 2 │
│ 2018-03-31 │ 2018-03-31 05:00:00 │ google.ru │ 20 │ 20 │ 20 │ 1 │
│ 2018-03-31 │ 2018-03-31 03:00:00 │ google.ru │ 10 │ 10 │ 10 │ 1 │
└──────────────┴─────────────────────┴─────────────┴───────────────────┴───────────────────┴───────────────────┴─────────────┘
SELECT count() FROM requests_graph;
┌─count()─┐
│ 4 │
└─────────┘
OPTIMIZE TABLE requests_graph;
SELECT count() FROM requests_graph;
┌─count()─┐
│ 3 │
└─────────┘
SELECT request_date,
request_hour,
request_uri,
avgMerge(avg_response_time) avg_response_time,
maxMerge(max_response_time) max_response_time,
minMerge(min_response_time) min_response_time,
countMerge(request_count) request_cnt
FROM requests_graph
GROUP BY request_date, request_hour, request_uri;
┌─request_date─┬────────request_hour─┬─request_uri─┬─avg_response_time─┬─max_response_time─┬─min_response_time─┬─request_cnt─┐
│ 2018-03-31 │ 2018-03-31 03:00:00 │ ya.ru │ 15 │ 20 │ 10 │ 2 │
│ 2018-03-31 │ 2018-03-31 05:00:00 │ google.ru │ 20 │ 20 │ 20 │ 1 │
│ 2018-03-31 │ 2018-03-31 03:00:00 │ google.ru │ 10 │ 10 │ 10 │ 1 │
└──────────────┴─────────────────────┴─────────────┴───────────────────┴───────────────────┴───────────────────┴─────────────┘
------------------------------------
# modern syntax and MV to
CREATE table requests_graph (
request_date Date,
request_hour DateTime('UTC'),
request_uri String,
avg_response_time AggregateFunction(avg, Int32),
max_response_time AggregateFunction(max, Int32),
min_response_time AggregateFunction(min, Int32),
request_count AggregateFunction(count)
) ENGINE = AggregatingMergeTree() Partition by toYYYYMM(request_date)
Order by (request_hour,request_uri);
CREATE MATERIALIZED VIEW requests_graph_mv
to requests_graph
AS SELECT
request_date,
toStartOfHour(request_time) request_hour,
request_uri,
avgState(response_time) avg_response_time,
maxState(response_time) max_response_time,
minState(response_time) min_response_time,
countState() request_count
FROM requests
GROUP BY request_date, request_hour, request_uri;
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