Sampling Example
The most important idea about sampling that the primary index must have LowCardinality. (For more information, see the Altinity Knowledge Base article on LowCardinality or a ClickHouse® user's lessons learned from LowCardinality).
The following example demonstrates how sampling can be setup correctly, and an example if it being set up incorrectly as a comparison.
Sampling requires sample by expression . This ensures a range of sampled column types fit within a specified range, which ensures the requirement of low cardinality. In this example, I cannot use transaction_id because I can not ensure that the min value of transaction_id = 0 and max value = MAX_UINT64. Instead, I used cityHash64(transaction_id)to expand the range within the minimum and maximum values.
For example if all values of transaction_id are from 0 to 10000 sampling will be inefficient. But cityHash64(transaction_id) expands the range from 0 to 18446744073709551615:
SELECT cityHash64(10000)
┌────cityHash64(10000)─┐
│ 14845905981091347439 │
└──────────────────────┘
If I used transaction_id without knowing that they matched the allowable ranges, the results of sampled queries would be skewed. For example, when using sample 0.5, ClickHouse requests where sample_col >= 0 and sample_col <= MAX_UINT64/2.
Also you can include multiple columns into a hash function of the sampling expression to improve randomness of the distribution cityHash64(transaction_id, banner_id).
Sampling Friendly Table
CREATE TABLE table_one
( timestamp UInt64,
transaction_id UInt64,
banner_id UInt16,
value UInt32
)
ENGINE = MergeTree()
PARTITION BY toYYYYMMDD(toDateTime(timestamp))
ORDER BY (banner_id,
toStartOfHour(toDateTime(timestamp)),
cityHash64(transaction_id))
SAMPLE BY cityHash64(transaction_id)
SETTINGS index_granularity = 8192
insert into table_one
select 1602809234+intDiv(number,100000),
number,
number%991,
toUInt32(rand())
from numbers(10000000000);
I reduced the granularity of the timestamp column to one hour with toStartOfHour(toDateTime(timestamp)) , otherwise sampling will not work.
Verifying Sampling Works
The following shows that sampling works with the table and parameters described above. Notice the Elapsed time when invoking sampling:
-- Q1. No where filters.
-- The query is 10 times faster with SAMPLE 0.01
select banner_id, sum(value), count(value), max(value)
from table_one
group by banner_id format Null;
0 rows in set. Elapsed: 11.490 sec.
Processed 10.00 billion rows, 60.00 GB (870.30 million rows/s., 5.22 GB/s.)
select banner_id, sum(value), count(value), max(value)
from table_one SAMPLE 0.01
group by banner_id format Null;
0 rows in set. Elapsed: 1.316 sec.
Processed 452.67 million rows, 6.34 GB (343.85 million rows/s., 4.81 GB/s.)
-- Q2. Filter by the first column in index (banner_id = 42)
-- The query is 20 times faster with SAMPLE 0.01
-- reads 20 times less rows: 10.30 million rows VS Processed 696.32 thousand rows
select banner_id, sum(value), count(value), max(value)
from table_one
WHERE banner_id = 42
group by banner_id format Null;
0 rows in set. Elapsed: 0.020 sec.
Processed 10.30 million rows, 61.78 MB (514.37 million rows/s., 3.09 GB/s.)
select banner_id, sum(value), count(value), max(value)
from table_one SAMPLE 0.01
WHERE banner_id = 42
group by banner_id format Null;
0 rows in set. Elapsed: 0.008 sec.
Processed 696.32 thousand rows, 9.75 MB (92.49 million rows/s., 1.29 GB/s.)
-- Q3. No filters
-- The query is 10 times faster with SAMPLE 0.01
-- reads 20 times less rows.
select banner_id,
toStartOfHour(toDateTime(timestamp)) hr,
sum(value), count(value), max(value)
from table_one
group by banner_id, hr format Null;
0 rows in set. Elapsed: 36.660 sec.
Processed 10.00 billion rows, 140.00 GB (272.77 million rows/s., 3.82 GB/s.)
select banner_id,
toStartOfHour(toDateTime(timestamp)) hr,
sum(value), count(value), max(value)
from table_one SAMPLE 0.01
group by banner_id, hr format Null;
0 rows in set. Elapsed: 3.741 sec.
Processed 452.67 million rows, 9.96 GB (121.00 million rows/s., 2.66 GB/s.)
-- Q4. Filter by not indexed column
-- The query is 6 times faster with SAMPLE 0.01
-- reads 20 times less rows.
select count()
from table_one
where value = 666 format Null;
1 rows in set. Elapsed: 6.056 sec.
Processed 10.00 billion rows, 40.00 GB (1.65 billion rows/s., 6.61 GB/s.)
select count()
from table_one SAMPLE 0.01
where value = 666 format Null;
1 rows in set. Elapsed: 1.214 sec.
Processed 452.67 million rows, 5.43 GB (372.88 million rows/s., 4.47 GB/s.)
Non-Sampling Friendly Table
CREATE TABLE table_one
( timestamp UInt64,
transaction_id UInt64,
banner_id UInt16,
value UInt32
)
ENGINE = MergeTree()
PARTITION BY toYYYYMMDD(toDateTime(timestamp))
ORDER BY (banner_id,
timestamp,
cityHash64(transaction_id))
SAMPLE BY cityHash64(transaction_id)
SETTINGS index_granularity = 8192
insert into table_one
select 1602809234+intDiv(number,100000),
number,
number%991,
toUInt32(rand())
from numbers(10000000000);
This is the same as our other table, BUT granularity of timestamp column is not reduced.
Verifying Sampling Does Not Work
The following tests shows that sampling is not working because of the lack of timestamp granularity. The Elapsed time is longer when sampling is used.
-- Q1. No where filters.
-- The query is 2 times SLOWER!!! with SAMPLE 0.01
-- Because it needs to read excessive column with sampling data!
select banner_id, sum(value), count(value), max(value)
from table_one
group by banner_id format Null;
0 rows in set. Elapsed: 11.196 sec.
Processed 10.00 billion rows, 60.00 GB (893.15 million rows/s., 5.36 GB/s.)
select banner_id, sum(value), count(value), max(value)
from table_one SAMPLE 0.01
group by banner_id format Null;
0 rows in set. Elapsed: 24.378 sec.
Processed 10.00 billion rows, 140.00 GB (410.21 million rows/s., 5.74 GB/s.)
-- Q2. Filter by the first column in index (banner_id = 42)
-- The query is SLOWER with SAMPLE 0.01
select banner_id, sum(value), count(value), max(value)
from table_one
WHERE banner_id = 42
group by banner_id format Null;
0 rows in set. Elapsed: 0.022 sec.
Processed 10.27 million rows, 61.64 MB (459.28 million rows/s., 2.76 GB/s.)
select banner_id, sum(value), count(value), max(value)
from table_one SAMPLE 0.01
WHERE banner_id = 42
group by banner_id format Null;
0 rows in set. Elapsed: 0.037 sec.
Processed 10.27 million rows, 143.82 MB (275.16 million rows/s., 3.85 GB/s.)
-- Q3. No filters
-- The query is SLOWER with SAMPLE 0.01
select banner_id,
toStartOfHour(toDateTime(timestamp)) hr,
sum(value), count(value), max(value)
from table_one
group by banner_id, hr format Null;
0 rows in set. Elapsed: 21.663 sec.
Processed 10.00 billion rows, 140.00 GB (461.62 million rows/s., 6.46 GB/s.)
select banner_id,
toStartOfHour(toDateTime(timestamp)) hr, sum(value),
count(value), max(value)
from table_one SAMPLE 0.01
group by banner_id, hr format Null;
0 rows in set. Elapsed: 26.697 sec.
Processed 10.00 billion rows, 220.00 GB (374.57 million rows/s., 8.24 GB/s.)
-- Q4. Filter by not indexed column
-- The query is SLOWER with SAMPLE 0.01
select count()
from table_one
where value = 666 format Null;
0 rows in set. Elapsed: 7.679 sec.
Processed 10.00 billion rows, 40.00 GB (1.30 billion rows/s., 5.21 GB/s.)
select count()
from table_one SAMPLE 0.01
where value = 666 format Null;
0 rows in set. Elapsed: 21.668 sec.
Processed 10.00 billion rows, 120.00 GB (461.51 million rows/s., 5.54 GB/s.)