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new a9159d8f96d docs: link fixes (#18308) (#18309)
a9159d8f96d is described below
commit a9159d8f96dc66f052b0b19fc3e6e9c3596ee061
Author: Victoria Lim <[email protected]>
AuthorDate: Tue Jul 22 18:45:19 2025 -0700
docs: link fixes (#18308) (#18309)
---
docs/development/extensions-core/datasketches-kll.md | 2 +-
docs/development/extensions-core/datasketches-quantiles.md | 4 ++--
docs/multi-stage-query/concepts.md | 4 ++--
docs/multi-stage-query/reference.md | 2 +-
docs/querying/sql-functions.md | 10 +++++-----
5 files changed, 11 insertions(+), 11 deletions(-)
diff --git a/docs/development/extensions-core/datasketches-kll.md
b/docs/development/extensions-core/datasketches-kll.md
index 5245f816d88..b8e372dc942 100644
--- a/docs/development/extensions-core/datasketches-kll.md
+++ b/docs/development/extensions-core/datasketches-kll.md
@@ -23,7 +23,7 @@ title: "DataSketches KLL Sketch module"
-->
-This module provides Apache Druid aggregators based on numeric quantiles
KllFloatsSketch and KllDoublesSketch from [Apache
DataSketches](https://datasketches.apache.org/) library. KLL quantiles sketch
is a mergeable streaming algorithm to estimate the distribution of values, and
approximately answer queries about the rank of a value, probability mass
function of the distribution (PMF) or histogram, cumulative distribution
function (CDF), and quantiles (median, min, max, 95th percentile a [...]
+This module provides Apache Druid aggregators based on numeric quantiles
KllFloatsSketch and KllDoublesSketch from [Apache
DataSketches](https://datasketches.apache.org/) library. KLL quantiles sketch
is a mergeable streaming algorithm to estimate the distribution of values, and
approximately answer queries about the rank of a value, probability mass
function of the distribution (PMF) or histogram, cumulative distribution
function (CDF), and quantiles (median, min, max, 95th percentile a [...]
There are three major modes of operation:
diff --git a/docs/development/extensions-core/datasketches-quantiles.md
b/docs/development/extensions-core/datasketches-quantiles.md
index 6f1962dd5e3..2b2b83a47a9 100644
--- a/docs/development/extensions-core/datasketches-quantiles.md
+++ b/docs/development/extensions-core/datasketches-quantiles.md
@@ -23,7 +23,7 @@ title: "DataSketches Quantiles Sketch module"
-->
-This module provides Apache Druid aggregators based on numeric quantiles
DoublesSketch from [Apache DataSketches](https://datasketches.apache.org/)
library. Quantiles sketch is a mergeable streaming algorithm to estimate the
distribution of values, and approximately answer queries about the rank of a
value, probability mass function of the distribution (PMF) or histogram,
cumulative distribution function (CDF), and quantiles (median, min, max, 95th
percentile and such). See [Quantiles Sk [...]
+This module provides Apache Druid aggregators based on numeric quantiles
DoublesSketch from [Apache DataSketches](https://datasketches.apache.org/)
library. Quantiles sketch is a mergeable streaming algorithm to estimate the
distribution of values, and approximately answer queries about the rank of a
value, probability mass function of the distribution (PMF) or histogram,
cumulative distribution function (CDF), and quantiles (median, min, max, 95th
percentile and such). See [Quantiles Sk [...]
There are three major modes of operation:
@@ -57,7 +57,7 @@ The result of the aggregation is a DoublesSketch that is the
union of all sketch
|`type`|This string should always be "quantilesDoublesSketch"|yes|
|`name`|String representing the output column to store sketch values.|yes|
|`fieldName`|A string for the name of the input field (can contain sketches or
raw numeric values).|yes|
-|`k`|Parameter that determines the accuracy and size of the sketch. Higher k
means higher accuracy but more space to store sketches. Must be a power of 2
from 2 to 32768. See [accuracy
information](https://datasketches.apache.org/docs/Quantiles/OrigQuantilesSketch)
in the DataSketches documentation for details.|no, defaults to 128|
+|`k`|Parameter that determines the accuracy and size of the sketch. Higher k
means higher accuracy but more space to store sketches. Must be a power of 2
from 2 to 32768. See [accuracy
information](https://datasketches.apache.org/docs/Quantiles/ClassicQuantilesSketch.html#accuracy-and-size)
in the DataSketches documentation for details.|no, defaults to 128|
|`maxStreamLength`|This parameter defines the number of items that can be
presented to each sketch before it may need to move from off-heap to on-heap
memory. This is relevant to query types that use off-heap memory, including
[TopN](../../querying/topnquery.md) and
[GroupBy](../../querying/groupbyquery.md). Ideally, should be set high enough
such that most sketches can stay off-heap.|no, defaults to 1000000000|
|`shouldFinalize`|Return the final double type representing the estimate
rather than the intermediate sketch type itself. In addition to controlling the
finalization of this aggregator, you can control whether all aggregators are
finalized with the query context parameters
[`finalize`](../../querying/query-context.md) and
[`sqlFinalizeOuterSketches`](../../querying/sql-query-context.md).|no, defaults
to `true`|
diff --git a/docs/multi-stage-query/concepts.md
b/docs/multi-stage-query/concepts.md
index 0042467a9df..dee6f80bdd4 100644
--- a/docs/multi-stage-query/concepts.md
+++ b/docs/multi-stage-query/concepts.md
@@ -189,8 +189,8 @@ available in the **Segments** view under the
**Partitioning** column.
For more information about syntax, see [`CLUSTERED
BY`](./reference.md#clustered-by).
For more information about the mechanics of clustering, refer to
-[Secondary partitioning](../ingestion/partitioning#secondary-partitioning) and
-[Sorting](../ingestion/partitioning#sorting).
+[Secondary partitioning](../ingestion/partitioning.md#secondary-partitioning)
and
+[Sorting](../ingestion/partitioning.md#sorting).
### Rollup
diff --git a/docs/multi-stage-query/reference.md
b/docs/multi-stage-query/reference.md
index 5e4e3a5a309..1bd82f00efe 100644
--- a/docs/multi-stage-query/reference.md
+++ b/docs/multi-stage-query/reference.md
@@ -403,7 +403,7 @@ The following table lists the context parameters for the
MSQ task engine:
| `sqlJoinAlgorithm` | SELECT, INSERT, REPLACE<br /><br />Algorithm to use for
JOIN. Use `broadcast` (the default) for broadcast hash join or `sortMerge` for
sort-merge join. Affects all JOIN operations in the query. This is a hint to
the MSQ engine and the actual joins in the query may proceed in a different way
than specified. See [Joins](#joins) for more details. | `broadcast` |
| `rowsInMemory` | INSERT or REPLACE<br /><br />Maximum number of rows to
store in memory at once before flushing to disk during the segment generation
process. Ignored for non-INSERT queries. In most cases, use the default value.
You may need to override the default if you run into one of the [known
issues](./known-issues.md) around memory usage. | 100,000 |
| `segmentSortOrder` | INSERT or REPLACE<br /><br />Normally, Druid sorts rows
in individual segments using `__time` first, followed by the [CLUSTERED
BY](#clustered-by) clause. When you set `segmentSortOrder`, Druid uses the
order from this context parameter instead. Provide the column list as
comma-separated values or as a JSON array in string form.<br />< br/>For
example, consider an INSERT query that uses `CLUSTERED BY country` and has
`segmentSortOrder` set to `__time,city,country`. [...]
-| `forceSegmentSortByTime` | INSERT or REPLACE<br /><br />When set to `true`
(the default), Druid prepends `__time` to [CLUSTERED BY](#clustered-by) when
determining the sort order for individual segments. Druid also requires that
`segmentSortOrder`, if provided, starts with `__time`.<br /><br />When set to
`false`, Druid uses the [CLUSTERED BY](#clustered-by) alone to determine the
sort order for individual segments, and does not require that
`segmentSortOrder` begin with `__time`. Sett [...]
+| `forceSegmentSortByTime` | INSERT or REPLACE<br /><br />When set to `true`
(the default), Druid prepends `__time` to [CLUSTERED BY](#clustered-by) when
determining the sort order for individual segments. Druid also requires that
`segmentSortOrder`, if provided, starts with `__time`.<br /><br />When set to
`false`, Druid uses the [CLUSTERED BY](#clustered-by) alone to determine the
sort order for individual segments, and does not require that
`segmentSortOrder` begin with `__time`. Sett [...]
| `maxParseExceptions`| SELECT, INSERT, REPLACE<br /><br />Maximum number of
parse exceptions that are ignored while executing the query before it stops
with `TooManyWarningsFault`. To ignore all the parse exceptions, set the value
to -1. | 0 |
| `rowsPerSegment` | INSERT or REPLACE<br /><br />The number of rows per
segment to target. The actual number of rows per segment may be somewhat higher
or lower than this number. In most cases, use the default. For general
information about sizing rows per segment, see [Segment Size
Optimization](../operations/segment-optimization.md). | 3,000,000 |
| `indexSpec` | INSERT or REPLACE<br /><br />An
[`indexSpec`](../ingestion/ingestion-spec.md#indexspec) to use when generating
segments. May be a JSON string or object. See [Front
coding](../ingestion/ingestion-spec.md#front-coding) for details on configuring
an `indexSpec` with front coding. | See
[`indexSpec`](../ingestion/ingestion-spec.md#indexspec). |
diff --git a/docs/querying/sql-functions.md b/docs/querying/sql-functions.md
index ce0ce53460f..9f75a96ce79 100644
--- a/docs/querying/sql-functions.md
+++ b/docs/querying/sql-functions.md
@@ -285,7 +285,7 @@ Returns the following:
## APPROX_COUNT_DISTINCT_DS_THETA
-Returns the approximate number of distinct values in a Theta sketch column or
a regular column. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta#aggregator) for a
description of optional parameters.
+Returns the approximate number of distinct values in a Theta sketch column or
a regular column. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta.md#aggregator) for a
description of optional parameters.
* **Syntax:** `APPROX_COUNT_DISTINCT_DS_THETA(expr, [size])`
* **Function type:** Aggregation
@@ -2305,7 +2305,7 @@ Returns a result similar to the following:
## DS_THETA
-Creates a Theta sketch on a column containing Theta sketches or a regular
column. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta#aggregator) for a
description of optional parameters.
+Creates a Theta sketch on a column containing Theta sketches or a regular
column. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta.md#aggregator) for a
description of optional parameters.
* **Syntax:** `DS_THETA(expr, [size])`
* **Function type:** Aggregation
@@ -5551,7 +5551,7 @@ Returns the following:
## THETA_SKETCH_INTERSECT
-Returns an intersection of Theta sketches. Each input expression must return a
Theta sketch. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta#aggregator) for a
description of optional parameters.
+Returns an intersection of Theta sketches. Each input expression must return a
Theta sketch. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta.md#aggregator) for a
description of optional parameters.
* **Syntax:** `THETA_SKETCH_INTERSECT([size], expr0, expr1, ...)`
* **Function type:** Scalar, sketch
@@ -5585,7 +5585,7 @@ Returns the following:
## THETA_SKETCH_NOT
-Returns a set difference of Theta sketches. Each input expression must return
a Theta sketch. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta#aggregator) for a
description of optional parameters.
+Returns a set difference of Theta sketches. Each input expression must return
a Theta sketch. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta.md#aggregator) for a
description of optional parameters.
* **Syntax:** `THETA_SKETCH_NOT([size], expr0, expr1, ...)`
* **Function type:** Scalar, sketch
@@ -5620,7 +5620,7 @@ Returns the following:
## THETA_SKETCH_UNION
-Returns a union of Theta sketches. Each input expression must return a Theta
sketch. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta#aggregator) for a
description of optional parameters.
+Returns a union of Theta sketches. Each input expression must return a Theta
sketch. See [DataSketches Theta Sketch
module](../development/extensions-core/datasketches-theta.md#aggregator) for a
description of optional parameters.
* **Syntax:**`THETA_SKETCH_UNION([size], expr0, expr1, ...)`
* **Function type:** Scalar, sketch
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