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Copy file name to clipboardExpand all lines: docs/en/sql-reference/aggregate-functions/parametric-functions.md
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@@ -104,7 +104,7 @@ Events that occur at the same second may lay in the sequence in an undefined ord
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**Parameters**
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-`pattern` — Pattern string. See [Pattern syntax](#sequencematch).
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-`pattern` — Pattern string. See [Pattern syntax](#pattern-syntax).
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**Returned values**
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Type: `UInt8`.
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<aname="sequence-function-pattern-syntax"></a>
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**Pattern syntax**
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#### Pattern syntax
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-`(?N)` — Matches the condition argument at position `N`. Conditions are numbered in the `[1, 32]` range. For example, `(?1)` matches the argument passed to the `cond1` parameter.
Copy file name to clipboardExpand all lines: docs/en/sql-reference/data-types/newjson.md
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@@ -453,8 +453,8 @@ As we can see, after inserting paths `e` and `f.g` the limit was reached and we
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### During merges of data parts in MergeTree table engines
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During merge of several data parts in MergeTree table the `JSON` column in the resulting data part can reach the limit of dynamic paths won't be able to store all paths from source parts as subcolumns.
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In this case ClickHouse chooses what paths will remain as subcolumns after merge and what types will be stored in the shared data structure. In most cases ClickHouse tries to keep paths that contains
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During merge of several data parts in MergeTree table the `JSON` column in the resulting data part can reach the limit of dynamic paths and won't be able to store all paths from source parts as subcolumns.
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In this case ClickHouse chooses what paths will remain as subcolumns after merge and what paths will be stored in the shared data structure. In most cases ClickHouse tries to keep paths that contain
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the largest number of non-null values and move the rarest paths to the shared data structure, but it depends on the implementation.
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Let's see an example of such merge. First, let's create a table with `JSON` column, set the limit of dynamic paths to `3` and insert values with `5` different paths:
Copy file name to clipboardExpand all lines: docs/en/sql-reference/functions/date-time-functions.md
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@@ -2019,7 +2019,7 @@ Alias: `dateTrunc`.
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`unit` argument is case-insensitive.
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-`value` — Date and time. [DateTime](../data-types/datetime.md) or [DateTime64](../data-types/datetime64.md).
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-`value` — Date and time. [Date](../data-types/date.md), [Date32](../data-types/date32.md), [DateTime](../data-types/datetime.md) or [DateTime64](../data-types/datetime64.md).
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-`timezone` — [Timezone name](../../operations/server-configuration-parameters/settings.md#server_configuration_parameters-timezone) for the returned value (optional). If not specified, the function uses the timezone of the `value` parameter. [String](../data-types/string.md).
// - Other formats (e.g. FORMAT CSV) are arbitrarily more complex and tricky to parse. For example, we may be unable to distinguish if the semicolon
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// is part of the data or ends the statement. In this case, we simply assume that the end of the INSERT statement is determined by \n\n (two newlines).
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auto * insert_ast = parsed_query->as<ASTInsertQuery>();
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// We also consider the INSERT query in EXPLAIN queries (same as normal INSERT queries)
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if (!insert_ast)
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{
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auto * explain_ast = parsed_query->as<ASTExplainQuery>();
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if (explain_ast && explain_ast->getExplainedQuery())
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