Fix ClickHouse characters case

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Romain Neutron 2021-05-27 21:49:41 +02:00
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commit d3be14e639
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8 changed files with 15 additions and 15 deletions

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@ -39,7 +39,7 @@ Question candidates:
- How to kill a process (query) in ClickHouse?
- How to implement pivot (like in pandas)?
- How to remove the default ClickHouse user through users.d?
- Importing MySQL dump to Clickhouse
- Importing MySQL dump to ClickHouse
- Window function workarounds (row_number, lag/lead, running diff/sum/average)
##}

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@ -502,12 +502,12 @@ The default `max_server_memory_usage` value is calculated as `memory_amount * ma
## max_server_memory_usage_to_ram_ratio {#max_server_memory_usage_to_ram_ratio}
Defines the fraction of total physical RAM amount, available to the Clickhouse server. If the server tries to utilize more, the memory is cut down to the appropriate amount.
Defines the fraction of total physical RAM amount, available to the ClickHouse server. If the server tries to utilize more, the memory is cut down to the appropriate amount.
Possible values:
- Positive double.
- 0 — The Clickhouse server can use all available RAM.
- 0 — The ClickHouse server can use all available RAM.
Default value: `0`.

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@ -455,15 +455,15 @@ Possible values:
- `simple` - Simple output format.
Clickhouse output date and time `YYYY-MM-DD hh:mm:ss` format. For example, `2019-08-20 10:18:56`. The calculation is performed according to the data type's time zone (if present) or server time zone.
ClickHouse output date and time `YYYY-MM-DD hh:mm:ss` format. For example, `2019-08-20 10:18:56`. The calculation is performed according to the data type's time zone (if present) or server time zone.
- `iso` - ISO output format.
Clickhouse output date and time in [ISO 8601](https://en.wikipedia.org/wiki/ISO_8601) `YYYY-MM-DDThh:mm:ssZ` format. For example, `2019-08-20T10:18:56Z`. Note that output is in UTC (`Z` means UTC).
ClickHouse output date and time in [ISO 8601](https://en.wikipedia.org/wiki/ISO_8601) `YYYY-MM-DDThh:mm:ssZ` format. For example, `2019-08-20T10:18:56Z`. Note that output is in UTC (`Z` means UTC).
- `unix_timestamp` - Unix timestamp output format.
Clickhouse output date and time in [Unix timestamp](https://en.wikipedia.org/wiki/Unix_time) format. For example `1566285536`.
ClickHouse output date and time in [Unix timestamp](https://en.wikipedia.org/wiki/Unix_time) format. For example `1566285536`.
Default value: `simple`.
@ -887,7 +887,7 @@ Higher values will lead to higher memory usage.
The maximum size of blocks of uncompressed data before compressing for writing to a table. By default, 1,048,576 (1 MiB). Specifying smaller block size generally leads to slightly reduced compression ratio, the compression and decompression speed increases slightly due to cache locality, and memory consumption is reduced.
!!! note "Warning"
This is an expert-level setting, and you shouldn't change it if you're just getting started with Clickhouse.
This is an expert-level setting, and you shouldn't change it if you're just getting started with ClickHouse.
Dont confuse blocks for compression (a chunk of memory consisting of bytes) with blocks for query processing (a set of rows from a table).
@ -904,7 +904,7 @@ We are writing a UInt32-type column (4 bytes per value). When writing 8192 rows,
We are writing a URL column with the String type (average size of 60 bytes per value). When writing 8192 rows, the average will be slightly less than 500 KB of data. Since this is more than 65,536, a compressed block will be formed for each mark. In this case, when reading data from the disk in the range of a single mark, extra data wont be decompressed.
!!! note "Warning"
This is an expert-level setting, and you shouldn't change it if you're just getting started with Clickhouse.
This is an expert-level setting, and you shouldn't change it if you're just getting started with ClickHouse.
## max_query_size {#settings-max_query_size}
@ -2672,7 +2672,7 @@ Possible values:
- `'DISTINCT'` — ClickHouse outputs rows as a result of combining queries removing duplicate rows.
- `'ALL'` — ClickHouse outputs all rows as a result of combining queries including duplicate rows.
- `''` — Clickhouse generates an exception when used with `UNION`.
- `''` — ClickHouse generates an exception when used with `UNION`.
Default value: `''`.

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@ -5,7 +5,7 @@ toc_title: Geo
# Geo Data Types {#geo-data-types}
Clickhouse supports data types for representing geographical objects — locations, lands, etc.
ClickHouse supports data types for representing geographical objects — locations, lands, etc.
!!! warning "Warning"
Currently geo data types are an experimental feature. To work with them you must set `allow_experimental_geo_types = 1`.

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@ -55,7 +55,7 @@ Functions:
## See Also {#see-also}
- [A Magical Mystery Tour of the LowCardinality Data Type](https://www.altinity.com/blog/2019/3/27/low-cardinality).
- [Reducing Clickhouse Storage Cost with the Low Cardinality Type Lessons from an Instana Engineer](https://www.instana.com/blog/reducing-clickhouse-storage-cost-with-the-low-cardinality-type-lessons-from-an-instana-engineer/).
- [Reducing ClickHouse Storage Cost with the Low Cardinality Type Lessons from an Instana Engineer](https://www.instana.com/blog/reducing-clickhouse-storage-cost-with-the-low-cardinality-type-lessons-from-an-instana-engineer/).
- [String Optimization (video presentation in Russian)](https://youtu.be/rqf-ILRgBdY?list=PL0Z2YDlm0b3iwXCpEFiOOYmwXzVmjJfEt). [Slides in English](https://github.com/yandex/clickhouse-presentations/raw/master/meetup19/string_optimization.pdf).
[Original article](https://clickhouse.tech/docs/en/sql-reference/data-types/lowcardinality/) <!--hide-->

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@ -153,7 +153,7 @@ Result:
Can be used with [MinHash](../../sql-reference/functions/hash-functions.md#ngramminhash) functions for detection of semi-duplicate strings:
``` sql
SELECT tupleHammingDistance(wordShingleMinHash(string), wordShingleMinHashCaseInsensitive(string)) as HammingDistance FROM (SELECT 'Clickhouse is a column-oriented database management system for online analytical processing of queries.' AS string);
SELECT tupleHammingDistance(wordShingleMinHash(string), wordShingleMinHashCaseInsensitive(string)) as HammingDistance FROM (SELECT 'ClickHouse is a column-oriented database management system for online analytical processing of queries.' AS string);
```
Result:

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@ -252,11 +252,11 @@ External sorting works much less effectively than sorting in RAM.
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](../../../operations/settings/settings.md#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](../../../sql-reference/statements/select/limit.md). So queries on big data with small limit are processed faster.
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](../../../sql-reference/statements/select/limit.md). 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](../../../sql-reference/statements/select/group-by.md) clause and [FINAL](../../../sql-reference/statements/select/from.md#select-from-final) modifier.
When the `optimize_read_in_order` setting is disabled, the Clickhouse server does not use the table index while processing `SELECT` queries.
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](../../../sql-reference/statements/select/where.md) condition that requires to read huge amount of records before queried data is found.

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@ -4,7 +4,7 @@ toc_title: WITH
# WITH Clause {#with-clause}
Clickhouse supports Common Table Expressions ([CTE](https://en.wikipedia.org/wiki/Hierarchical_and_recursive_queries_in_SQL)), that is provides to use results of `WITH` clause in the rest of `SELECT` query. Named subqueries can be included to the current and child query context in places where table objects are allowed. Recursion is prevented by hiding the current level CTEs from the WITH expression.
ClickHouse supports Common Table Expressions ([CTE](https://en.wikipedia.org/wiki/Hierarchical_and_recursive_queries_in_SQL)), that is provides to use results of `WITH` clause in the rest of `SELECT` query. Named subqueries can be included to the current and child query context in places where table objects are allowed. Recursion is prevented by hiding the current level CTEs from the WITH expression.
## Syntax