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new 4e5f9cd Add pushes to DataSketches in SQL docs. (#11578)
4e5f9cd is described below
commit 4e5f9cdacf43248abdb2d1b632e30b3962957b72
Author: Gian Merlino <[email protected]>
AuthorDate: Mon Aug 16 10:38:56 2021 -0700
Add pushes to DataSketches in SQL docs. (#11578)
* Add pushes to DataSketches in SQL docs.
These notices were already in the native docs, but they were missing
from the SQL docs.
* Grammar fix.
---
docs/querying/sql.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/docs/querying/sql.md b/docs/querying/sql.md
index 50706b3..371832c 100644
--- a/docs/querying/sql.md
+++ b/docs/querying/sql.md
@@ -333,12 +333,12 @@ Only the COUNT, ARRAY_AGG, and STRING_AGG aggregations
can accept the DISTINCT k
|`MIN(expr)`|Takes the minimum of numbers.|`null` if
`druid.generic.useDefaultValueForNull=false`, otherwise `9223372036854775807`
(maximum LONG value)|
|`MAX(expr)`|Takes the maximum of numbers.|`null` if
`druid.generic.useDefaultValueForNull=false`, otherwise `-9223372036854775808`
(minimum LONG value)|
|`AVG(expr)`|Averages numbers.|`null` if
`druid.generic.useDefaultValueForNull=false`, otherwise `0`|
-|`APPROX_COUNT_DISTINCT(expr)`|Counts distinct values of expr, which can be a
regular column or a hyperUnique column. This is always approximate, regardless
of the value of "useApproximateCountDistinct". This uses Druid's built-in
"cardinality" or "hyperUnique" aggregators. See also `COUNT(DISTINCT
expr)`.|`0`|
+|`APPROX_COUNT_DISTINCT(expr)`|_Usage note:_ consider using
`APPROX_COUNT_DISTINCT_DS_HLL` instead, which offers better accuracy in many
cases.<br/><br/>Counts distinct values of expr, which can be a regular column
or a hyperUnique column. This is always approximate, regardless of the value of
"useApproximateCountDistinct". This uses Druid's built-in "cardinality" or
"hyperUnique" aggregators. See also `COUNT(DISTINCT expr)`.|`0`|
|`APPROX_COUNT_DISTINCT_DS_HLL(expr, [lgK, tgtHllType])`|Counts distinct
values of `expr`, which can be a regular column or an [HLL
sketch](../development/extensions-core/datasketches-hll.md) column. Results are
always approximate, regardless of the value of
[`useApproximateCountDistinct`](../querying/sql.html#connection-context). The
`lgK` and `tgtHllType` parameters here are, like the equivalents in the
[aggregator](../development/extensions-core/datasketches-hll.html#aggregators),
des [...]
|`APPROX_COUNT_DISTINCT_DS_THETA(expr, [size])`|Counts distinct values of
expr, which can be a regular column or a [Theta
sketch](../development/extensions-core/datasketches-theta.md) column. This is
always approximate, regardless of the value of
[`useApproximateCountDistinct`](../querying/sql.html#connection-context). The
`size` parameter is described in the Theta sketch documentation. The
[DataSketches
extension](../development/extensions-core/datasketches-extension.md) must be
loaded [...]
|`DS_HLL(expr, [lgK, tgtHllType])`|Creates an [HLL
sketch](../development/extensions-core/datasketches-hll.md) on the values of
expr, which can be a regular column or a column containing HLL sketches. The
`lgK` and `tgtHllType` parameters are described in the HLL sketch
documentation. The [DataSketches
extension](../development/extensions-core/datasketches-extension.md) must be
loaded to use this function.|`'0'` (STRING)|
|`DS_THETA(expr, [size])`|Creates a [Theta
sketch](../development/extensions-core/datasketches-theta.md) on the values of
expr, which can be a regular column or a column containing Theta sketches. The
`size` parameter is described in the Theta sketch documentation. The
[DataSketches
extension](../development/extensions-core/datasketches-extension.md) must be
loaded to use this function.|`'0.0'` (STRING)|
-|`APPROX_QUANTILE(expr, probability, [resolution])`|Computes approximate
quantiles on numeric or
[approxHistogram](../development/extensions-core/approximate-histograms.md#approximate-histogram-aggregator)
exprs. The "probability" should be between 0 and 1 (exclusive). The
"resolution" is the number of centroids to use for the computation. Higher
resolutions will give more precise results but also have higher overhead. If
not provided, the default resolution is 50. The [approximate histo [...]
+|`APPROX_QUANTILE(expr, probability, [resolution])`|_Deprecated._ Use
`APPROX_QUANTILE_DS` instead, which provides a superior
distribution-independent algorithm with formal error
guarantees.<br/><br/>Computes approximate quantiles on numeric or
[approxHistogram](../development/extensions-core/approximate-histograms.md#approximate-histogram-aggregator)
exprs. The "probability" should be between 0 and 1 (exclusive). The
"resolution" is the number of centroids to use for the computation. Hi [...]
|`APPROX_QUANTILE_DS(expr, probability, [k])`|Computes approximate quantiles
on numeric or [Quantiles
sketch](../development/extensions-core/datasketches-quantiles.md) exprs. The
"probability" should be between 0 and 1 (exclusive). The `k` parameter is
described in the Quantiles sketch documentation. The [DataSketches
extension](../development/extensions-core/datasketches-extension.md) must be
loaded to use this function.|`NaN`|
|`APPROX_QUANTILE_FIXED_BUCKETS(expr, probability, numBuckets, lowerLimit,
upperLimit, [outlierHandlingMode])`|Computes approximate quantiles on numeric
or [fixed buckets
histogram](../development/extensions-core/approximate-histograms.md#fixed-buckets-histogram)
exprs. The "probability" should be between 0 and 1 (exclusive). The
`numBuckets`, `lowerLimit`, `upperLimit`, and `outlierHandlingMode` parameters
are described in the fixed buckets histogram documentation. The [approximate
hist [...]
|`DS_QUANTILES_SKETCH(expr, [k])`|Creates a [Quantiles
sketch](../development/extensions-core/datasketches-quantiles.md) on the values
of expr, which can be a regular column or a column containing quantiles
sketches. The `k` parameter is described in the Quantiles sketch documentation.
The [DataSketches
extension](../development/extensions-core/datasketches-extension.md) must be
loaded to use this function.|`'0'` (STRING)|
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