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Update argmin.md
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@ -6,7 +6,7 @@ sidebar_position: 105
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# argMin
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Calculates the `arg` value for a minimum `val` value. If there are several different values of `arg` for minimum values of `val`, returns the first of these values encountered.
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Both parts the `arg` and the `min` behave as [aggregate functions](../index.md), they both [skip `Null`](../index.md#null-processing) during processing and return not-Null values if not-Null values are available.
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Both parts the `arg` and the `min` behave as [aggregate functions](../index.md), they both [skip `Null`](../index.md#null-processing) during processing and return not Null values if not Null values are available.
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**Syntax**
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@ -90,7 +90,7 @@ select (argMin((a, b), b) as t).1 argMinA, t.2 argMinB from test;
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select argMin(a, b), min(b) from test where a is Null and b is Null;
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┌─argMin(a, b)─┬─min(b)─┐
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│ ᴺᵁᴸᴸ │ ᴺᵁᴸᴸ │ -- ll aggregated rows contains at least one `NULL` value because of the filter, so all rows are skipped, therefore the result will be `NULL`
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│ ᴺᵁᴸᴸ │ ᴺᵁᴸᴸ │ -- All aggregated rows contains at least one `NULL` value because of the filter, so all rows are skipped, therefore the result will be `NULL`
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└──────────────┴────────┘
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select argMin(a, (b, a)), min(tuple(b, a)) from test;
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@ -100,7 +100,7 @@ select argMin(a, (b, a)), min(tuple(b, a)) from test;
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select argMin((a, b), (b, a)), min(tuple(b, a)) from test;
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┌─argMin(tuple(a, b), tuple(b, a))─┬─min(tuple(b, a))─┐
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│ (NULL,NULL) │ (NULL,NULL) │
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│ (NULL,NULL) │ (NULL,NULL) │ -- argMin returns (NULL,NULL) here because Tuple allows to don't skip Nulls and min(tuple(b, a)) in this case is minimal value for this dataset
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└──────────────────────────────────┴──────────────────┘
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select argMin(a, tuple(b)) from test;
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