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ORDER BY |
ORDER BY Clause
The ORDER BY
clause contains a list of expressions, which can each be attributed with DESC
(descending) or ASC
(ascending) modifier which determine the sorting direction. If the direction is not specified, ASC
is assumed, so it’s usually omitted. The sorting direction applies to a single expression, not to the entire list. Example: ORDER BY Visits DESC, SearchPhrase
Rows that have identical values for the list of sorting expressions are output in an arbitrary order, which can also be non-deterministic (different each time). If the ORDER BY clause is omitted, the order of the rows is also undefined, and may be non-deterministic as well.
Sorting of Special Values
There are two approaches to NaN
and NULL
sorting order:
- By default or with the
NULLS LAST
modifier: first the values, thenNaN
, thenNULL
. - With the
NULLS FIRST
modifier: firstNULL
, thenNaN
, then other values.
Example
For the table
┌─x─┬────y─┐
│ 1 │ ᴺᵁᴸᴸ │
│ 2 │ 2 │
│ 1 │ nan │
│ 2 │ 2 │
│ 3 │ 4 │
│ 5 │ 6 │
│ 6 │ nan │
│ 7 │ ᴺᵁᴸᴸ │
│ 6 │ 7 │
│ 8 │ 9 │
└───┴──────┘
Run the query SELECT * FROM t_null_nan ORDER BY y NULLS FIRST
to get:
┌─x─┬────y─┐
│ 1 │ ᴺᵁᴸᴸ │
│ 7 │ ᴺᵁᴸᴸ │
│ 1 │ nan │
│ 6 │ nan │
│ 2 │ 2 │
│ 2 │ 2 │
│ 3 │ 4 │
│ 5 │ 6 │
│ 6 │ 7 │
│ 8 │ 9 │
└───┴──────┘
When floating point numbers are sorted, NaNs are separate from the other values. Regardless of the sorting order, NaNs come at the end. In other words, for ascending sorting they are placed as if they are larger than all the other numbers, while for descending sorting they are placed as if they are smaller than the rest.
Collation Support
For sorting by String values, you can specify collation (comparison). Example: ORDER BY SearchPhrase COLLATE 'tr'
- for sorting by keyword in ascending order, using the Turkish alphabet, case insensitive, assuming that strings are UTF-8 encoded. COLLATE
can be specified or not for each expression in ORDER BY independently. If ASC
or DESC
is specified, COLLATE
is specified after it. When using COLLATE
, sorting is always case-insensitive.
Collate is supported in LowCardinality, Nullable, Array and Tuple.
We only recommend using COLLATE
for final sorting of a small number of rows, since sorting with COLLATE
is less efficient than normal sorting by bytes.
Collation Examples
Example only with String values:
Input table:
┌─x─┬─s────┐
│ 1 │ bca │
│ 2 │ ABC │
│ 3 │ 123a │
│ 4 │ abc │
│ 5 │ BCA │
└───┴──────┘
Query:
SELECT * FROM collate_test ORDER BY s ASC COLLATE 'en';
Result:
┌─x─┬─s────┐
│ 3 │ 123a │
│ 4 │ abc │
│ 2 │ ABC │
│ 1 │ bca │
│ 5 │ BCA │
└───┴──────┘
Example with Nullable:
Input table:
┌─x─┬─s────┐
│ 1 │ bca │
│ 2 │ ᴺᵁᴸᴸ │
│ 3 │ ABC │
│ 4 │ 123a │
│ 5 │ abc │
│ 6 │ ᴺᵁᴸᴸ │
│ 7 │ BCA │
└───┴──────┘
Query:
SELECT * FROM collate_test ORDER BY s ASC COLLATE 'en';
Result:
┌─x─┬─s────┐
│ 4 │ 123a │
│ 5 │ abc │
│ 3 │ ABC │
│ 1 │ bca │
│ 7 │ BCA │
│ 6 │ ᴺᵁᴸᴸ │
│ 2 │ ᴺᵁᴸᴸ │
└───┴──────┘
Example with Array:
Input table:
┌─x─┬─s─────────────┐
│ 1 │ ['Z'] │
│ 2 │ ['z'] │
│ 3 │ ['a'] │
│ 4 │ ['A'] │
│ 5 │ ['z','a'] │
│ 6 │ ['z','a','a'] │
│ 7 │ [''] │
└───┴───────────────┘
Query:
SELECT * FROM collate_test ORDER BY s ASC COLLATE 'en';
Result:
┌─x─┬─s─────────────┐
│ 7 │ [''] │
│ 3 │ ['a'] │
│ 4 │ ['A'] │
│ 2 │ ['z'] │
│ 5 │ ['z','a'] │
│ 6 │ ['z','a','a'] │
│ 1 │ ['Z'] │
└───┴───────────────┘
Example with LowCardinality string:
Input table:
┌─x─┬─s───┐
│ 1 │ Z │
│ 2 │ z │
│ 3 │ a │
│ 4 │ A │
│ 5 │ za │
│ 6 │ zaa │
│ 7 │ │
└───┴─────┘
Query:
SELECT * FROM collate_test ORDER BY s ASC COLLATE 'en';
Result:
┌─x─┬─s───┐
│ 7 │ │
│ 3 │ a │
│ 4 │ A │
│ 2 │ z │
│ 1 │ Z │
│ 5 │ za │
│ 6 │ zaa │
└───┴─────┘
Example with Tuple:
┌─x─┬─s───────┐
│ 1 │ (1,'Z') │
│ 2 │ (1,'z') │
│ 3 │ (1,'a') │
│ 4 │ (2,'z') │
│ 5 │ (1,'A') │
│ 6 │ (2,'Z') │
│ 7 │ (2,'A') │
└───┴─────────┘
Query:
SELECT * FROM collate_test ORDER BY s ASC COLLATE 'en';
Result:
┌─x─┬─s───────┐
│ 3 │ (1,'a') │
│ 5 │ (1,'A') │
│ 2 │ (1,'z') │
│ 1 │ (1,'Z') │
│ 7 │ (2,'A') │
│ 4 │ (2,'z') │
│ 6 │ (2,'Z') │
└───┴─────────┘
Implementation Details
Less RAM is used if a small enough LIMIT is specified in addition to ORDER BY
. Otherwise, the amount of memory spent is proportional to the volume of data for sorting. For distributed query processing, if GROUP BY is omitted, sorting is partially done on remote servers, and the results are merged on the requestor server. This means that for distributed sorting, the volume of data to sort can be greater than the amount of memory on a single server.
If there is not enough RAM, it is possible to perform sorting in external memory (creating temporary files on a disk). Use the setting max_bytes_before_external_sort
for this purpose. If it is set to 0 (the default), external sorting is disabled. If it is enabled, when the volume of data to sort reaches the specified number of bytes, the collected data is sorted and dumped into a temporary file. After all data is read, all the sorted files are merged and the results are output. Files are written to the /var/lib/clickhouse/tmp/
directory in the config (by default, but you can use the tmp_path
parameter to change this setting).
Running a query may use more memory than max_bytes_before_external_sort
. For this reason, this setting must have a value significantly smaller than max_memory_usage
. As an example, if your server has 128 GB of RAM and you need to run a single query, set max_memory_usage
to 100 GB, and max_bytes_before_external_sort
to 80 GB.
External sorting works much less effectively than sorting in RAM.
Optimization of Data Reading
If ORDER BY
expression has a prefix that coincides with the table sorting key, you can optimize the query by using the optimize_read_in_order setting.
When the optimize_read_in_order
setting is enabled, the ClickHouse server uses the table index and reads the data in order of the ORDER BY
key. This allows to avoid reading all data in case of specified LIMIT. So queries on big data with small limit are processed faster.
Optimization works with both ASC
and DESC
and does not work together with GROUP BY clause and FINAL modifier.
When the optimize_read_in_order
setting is disabled, the ClickHouse server does not use the table index while processing SELECT
queries.
Consider disabling optimize_read_in_order
manually, when running queries that have ORDER BY
clause, large LIMIT
and WHERE condition that requires to read huge amount of records before queried data is found.
Optimization is supported in the following table engines:
- MergeTree
- Merge, Buffer, and MaterializedView table engines over
MergeTree
-engine tables
In MaterializedView
-engine tables the optimization works with views like SELECT ... FROM merge_tree_table ORDER BY pk
. But it is not supported in the queries like SELECT ... FROM view ORDER BY pk
if the view query does not have the ORDER BY
clause.
ORDER BY Expr WITH FILL Modifier
This modifier also can be combined with LIMIT … WITH TIES modifier.
WITH FILL
modifier can be set after ORDER BY expr
with optional FROM expr
, TO expr
and STEP expr
parameters.
All missed values of expr
column will be filled sequentially and other columns will be filled as defaults.
Use following syntax for filling multiple columns add WITH FILL
modifier with optional parameters after each field name in ORDER BY
section.
ORDER BY expr [WITH FILL] [FROM const_expr] [TO const_expr] [STEP const_numeric_expr], ... exprN [WITH FILL] [FROM expr] [TO expr] [STEP numeric_expr]
WITH FILL
can be applied only for fields with Numeric (all kind of float, decimal, int) or Date/DateTime types.
When FROM const_expr
not defined sequence of filling use minimal expr
field value from ORDER BY
.
When TO const_expr
not defined sequence of filling use maximum expr
field value from ORDER BY
.
When STEP const_numeric_expr
defined then const_numeric_expr
interprets as is
for numeric types as days
for Date type and as seconds
for DateTime type.
When STEP const_numeric_expr
omitted then sequence of filling use 1.0
for numeric type, 1 day
for Date type and 1 second
for DateTime type.
For example, the following query
SELECT n, source FROM (
SELECT toFloat32(number % 10) AS n, 'original' AS source
FROM numbers(10) WHERE number % 3 = 1
) ORDER BY n
returns
┌─n─┬─source───┐
│ 1 │ original │
│ 4 │ original │
│ 7 │ original │
└───┴──────────┘
but after apply WITH FILL
modifier
SELECT n, source FROM (
SELECT toFloat32(number % 10) AS n, 'original' AS source
FROM numbers(10) WHERE number % 3 = 1
) ORDER BY n WITH FILL FROM 0 TO 5.51 STEP 0.5
returns
┌───n─┬─source───┐
│ 0 │ │
│ 0.5 │ │
│ 1 │ original │
│ 1.5 │ │
│ 2 │ │
│ 2.5 │ │
│ 3 │ │
│ 3.5 │ │
│ 4 │ original │
│ 4.5 │ │
│ 5 │ │
│ 5.5 │ │
│ 7 │ original │
└─────┴──────────┘
For the case when we have multiple fields ORDER BY field2 WITH FILL, field1 WITH FILL
order of filling will follow the order of fields in ORDER BY
clause.
Example:
SELECT
toDate((number * 10) * 86400) AS d1,
toDate(number * 86400) AS d2,
'original' AS source
FROM numbers(10)
WHERE (number % 3) = 1
ORDER BY
d2 WITH FILL,
d1 WITH FILL STEP 5;
returns
┌───d1───────┬───d2───────┬─source───┐
│ 1970-01-11 │ 1970-01-02 │ original │
│ 1970-01-01 │ 1970-01-03 │ │
│ 1970-01-01 │ 1970-01-04 │ │
│ 1970-02-10 │ 1970-01-05 │ original │
│ 1970-01-01 │ 1970-01-06 │ │
│ 1970-01-01 │ 1970-01-07 │ │
│ 1970-03-12 │ 1970-01-08 │ original │
└────────────┴────────────┴──────────┘
Field d1
does not fill and use default value cause we do not have repeated values for d2
value, and sequence for d1
can’t be properly calculated.
The following query with a changed field in ORDER BY
SELECT
toDate((number * 10) * 86400) AS d1,
toDate(number * 86400) AS d2,
'original' AS source
FROM numbers(10)
WHERE (number % 3) = 1
ORDER BY
d1 WITH FILL STEP 5,
d2 WITH FILL;
returns
┌───d1───────┬───d2───────┬─source───┐
│ 1970-01-11 │ 1970-01-02 │ original │
│ 1970-01-16 │ 1970-01-01 │ │
│ 1970-01-21 │ 1970-01-01 │ │
│ 1970-01-26 │ 1970-01-01 │ │
│ 1970-01-31 │ 1970-01-01 │ │
│ 1970-02-05 │ 1970-01-01 │ │
│ 1970-02-10 │ 1970-01-05 │ original │
│ 1970-02-15 │ 1970-01-01 │ │
│ 1970-02-20 │ 1970-01-01 │ │
│ 1970-02-25 │ 1970-01-01 │ │
│ 1970-03-02 │ 1970-01-01 │ │
│ 1970-03-07 │ 1970-01-01 │ │
│ 1970-03-12 │ 1970-01-08 │ original │
└────────────┴────────────┴──────────┘