techdocsmith commented on code in PR #13524:
URL: https://github.com/apache/druid/pull/13524#discussion_r1051165775


##########
docs/development/extensions-core/datasketches-hll.md:
##########
@@ -23,29 +23,32 @@ title: "DataSketches HLL Sketch module"
   -->
 
 
-This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregator to 
produce a union of sketch columns in the same row.
-You can use the HLL sketch aggregator on columns of any identifiers. It will 
return estimated cardinality of the column.
+This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregators to 
produce a union of sketch columns in the same row.

Review Comment:
   ```suggestion
   This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
store in Druid segments. By default, Druid reads and merges sketches at query 
time. The default result is 
    the estimate of the number of distinct values presented to the sketch. You 
can also use post aggregators to produce a union of sketch columns in the same 
row.
   ```



##########
docs/development/extensions-core/datasketches-hll.md:
##########
@@ -23,29 +23,32 @@ title: "DataSketches HLL Sketch module"
   -->
 
 
-This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregator to 
produce a union of sketch columns in the same row.
-You can use the HLL sketch aggregator on columns of any identifiers. It will 
return estimated cardinality of the column.
+This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregators to 
produce a union of sketch columns in the same row.
+You can use the HLL sketch aggregator on any column to estimate its 
cardinality.
 
 To use this aggregator, make sure you 
[include](../../development/extensions.md#loading-extensions) the extension in 
your config file:
 
 ```
 druid.extensions.loadList=["druid-datasketches"]
 ```
 
-### Aggregators
+For additional sketch types supported in Druid, see [DataSketches 
extension](datasketches-extension.md).
 
-|property|description|required?|
+## Aggregators
+
+|Property|Description|Required?|
 |--------|-----------|---------|
-|`type`|This String should be [`HLLSketchBuild`](#hllsketchbuild-aggregator) 
or [`HLLSketchMerge`](#hllsketchmerge-aggregator)|yes|
-|`name`|A String for the output (result) name of the calculation.|yes|
-|`fieldName`|A String for the name of the input field.|yes|
+|`type`|This string should be [`HLLSketchBuild`](#hllsketchbuild-aggregator) 
or [`HLLSketchMerge`](#hllsketchmerge-aggregator).|yes|
+|`name`|A string for the output (result) name of the calculation.|yes|
+|`fieldName`|A string for the name of the input field.|yes|

Review Comment:
   ```suggestion
   |`fieldName`|The name of the input field.|yes|
   ```



##########
docs/development/extensions-core/datasketches-hll.md:
##########
@@ -23,29 +23,32 @@ title: "DataSketches HLL Sketch module"
   -->
 
 
-This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregator to 
produce a union of sketch columns in the same row.
-You can use the HLL sketch aggregator on columns of any identifiers. It will 
return estimated cardinality of the column.
+This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregators to 
produce a union of sketch columns in the same row.
+You can use the HLL sketch aggregator on any column to estimate its 
cardinality.
 
 To use this aggregator, make sure you 
[include](../../development/extensions.md#loading-extensions) the extension in 
your config file:
 
 ```
 druid.extensions.loadList=["druid-datasketches"]
 ```
 
-### Aggregators
+For additional sketch types supported in Druid, see [DataSketches 
extension](datasketches-extension.md).
 
-|property|description|required?|
+## Aggregators
+
+|Property|Description|Required?|
 |--------|-----------|---------|
-|`type`|This String should be [`HLLSketchBuild`](#hllsketchbuild-aggregator) 
or [`HLLSketchMerge`](#hllsketchmerge-aggregator)|yes|
-|`name`|A String for the output (result) name of the calculation.|yes|
-|`fieldName`|A String for the name of the input field.|yes|
+|`type`|This string should be [`HLLSketchBuild`](#hllsketchbuild-aggregator) 
or [`HLLSketchMerge`](#hllsketchmerge-aggregator).|yes|

Review Comment:
   ```suggestion
   |`type`|Either [`HLLSketchBuild`](#hllsketchbuild-aggregator) or 
[`HLLSketchMerge`](#hllsketchmerge-aggregator).|yes|
   ```



##########
docs/development/extensions-core/datasketches-theta.md:
##########
@@ -45,17 +50,18 @@ druid.extensions.loadList=["druid-datasketches"]
  }
 ```
 
-|property|description|required?|
+|Property|Description|Required?|
 |--------|-----------|---------|
-|type|This String should always be "thetaSketch"|yes|
-|name|A String for the output (result) name of the calculation.|yes|
-|fieldName|A String for the name of the aggregator used at ingestion time.|yes|
-|isInputThetaSketch|This should only be used at indexing time if your input 
data contains theta sketch objects. This would be the case if you use 
datasketches library outside of Druid, say with Pig/Hive, to produce the data 
that you are ingesting into Druid |no, defaults to false|
-|size|Must be a power of 2. Internally, size refers to the maximum number of 
entries sketch object will retain. Higher size means higher accuracy but more 
space to store sketches. Note that after you index with a particular size, 
druid will persist sketch in segments and you will use size greater or equal to 
that at query time. See the [DataSketches 
site](https://datasketches.apache.org/docs/Theta/ThetaSize) for details. In 
general, We recommend just sticking to default size. |no, defaults to 16384|
+|`type`|This string should always be "thetaSketch"|yes|
+|`name`|A string for the output (result) name of the calculation.|yes|

Review Comment:
   ```suggestion
   `name`|String representing the output column to store sketch values.|yes|
   ```



##########
docs/development/extensions-core/datasketches-theta.md:
##########
@@ -45,17 +50,18 @@ druid.extensions.loadList=["druid-datasketches"]
  }
 ```
 
-|property|description|required?|
+|Property|Description|Required?|
 |--------|-----------|---------|
-|type|This String should always be "thetaSketch"|yes|
-|name|A String for the output (result) name of the calculation.|yes|
-|fieldName|A String for the name of the aggregator used at ingestion time.|yes|
-|isInputThetaSketch|This should only be used at indexing time if your input 
data contains theta sketch objects. This would be the case if you use 
datasketches library outside of Druid, say with Pig/Hive, to produce the data 
that you are ingesting into Druid |no, defaults to false|
-|size|Must be a power of 2. Internally, size refers to the maximum number of 
entries sketch object will retain. Higher size means higher accuracy but more 
space to store sketches. Note that after you index with a particular size, 
druid will persist sketch in segments and you will use size greater or equal to 
that at query time. See the [DataSketches 
site](https://datasketches.apache.org/docs/Theta/ThetaSize) for details. In 
general, We recommend just sticking to default size. |no, defaults to 16384|
+|`type`|This string should always be "thetaSketch"|yes|
+|`name`|A string for the output (result) name of the calculation.|yes|
+|`fieldName`|A string for the name of the aggregator used at ingestion 
time.|yes|
+|`isInputThetaSketch`|This should only be used at indexing time if your input 
data contains theta sketch objects. This would be the case if you use 
datasketches library outside of Druid, say with Pig/Hive, to produce the data 
that you are ingesting into Druid |no, defaults to false|
+|`size`|Must be a power of 2. Internally, size refers to the maximum number of 
entries sketch object will retain. Higher size means higher accuracy but more 
space to store sketches. Note that after you index with a particular size, 
druid will persist sketch in segments and you will use size greater or equal to 
that at query time. See the [DataSketches 
site](https://datasketches.apache.org/docs/Theta/ThetaSize) for details. In 
general, We recommend just sticking to default size. |no, defaults to 16384|

Review Comment:
   ```suggestion
   |`size`|Must be a power of 2. Internally, size refers to the maximum number 
of entries sketch object retains. Higher size means higher accuracy but more 
space to store sketches. After you index with a particular size, Druid persists 
the sketch in segments. At query time you must use a size greater or equal to 
the ingested size. See the [DataSketches 
site](https://datasketches.apache.org/docs/Theta/ThetaSize) for details. The 
default is recommended for the majority of use cases. |no, defaults to 16384|
   ```



##########
docs/development/extensions-core/datasketches-hll.md:
##########
@@ -23,29 +23,32 @@ title: "DataSketches HLL Sketch module"
   -->
 
 
-This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregator to 
produce a union of sketch columns in the same row.
-You can use the HLL sketch aggregator on columns of any identifiers. It will 
return estimated cardinality of the column.
+This module provides Apache Druid aggregators for distinct counting based on 
HLL sketch from [Apache DataSketches](https://datasketches.apache.org/) 
library. At ingestion time, this aggregator creates the HLL sketch objects to 
be stored in Druid segments. At query time, sketches are read and merged 
together. In the end, by default, you receive the estimate of the number of 
distinct values presented to the sketch. Also, you can use post aggregators to 
produce a union of sketch columns in the same row.
+You can use the HLL sketch aggregator on any column to estimate its 
cardinality.
 
 To use this aggregator, make sure you 
[include](../../development/extensions.md#loading-extensions) the extension in 
your config file:
 
 ```
 druid.extensions.loadList=["druid-datasketches"]
 ```
 
-### Aggregators
+For additional sketch types supported in Druid, see [DataSketches 
extension](datasketches-extension.md).
 
-|property|description|required?|
+## Aggregators
+
+|Property|Description|Required?|
 |--------|-----------|---------|
-|`type`|This String should be [`HLLSketchBuild`](#hllsketchbuild-aggregator) 
or [`HLLSketchMerge`](#hllsketchmerge-aggregator)|yes|
-|`name`|A String for the output (result) name of the calculation.|yes|
-|`fieldName`|A String for the name of the input field.|yes|
+|`type`|This string should be [`HLLSketchBuild`](#hllsketchbuild-aggregator) 
or [`HLLSketchMerge`](#hllsketchmerge-aggregator).|yes|
+|`name`|A string for the output (result) name of the calculation.|yes|

Review Comment:
   ```suggestion
   `name`|String representing the output column to store sketch values.|yes|
   ```



##########
docs/development/extensions-core/datasketches-kll.md:
##########
@@ -50,17 +52,17 @@ The result of the aggregation is a KllFloatsSketch or 
KllDoublesSketch that is t
  }
 ```
 
-|property|description|required?|
+|Property|Description|Required?|
 |--------|-----------|---------|
-|type|This String should be "KllFloatsSketch" or "KllDoublesSketch"|yes|
-|name|A String for the output (result) name of the calculation.|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 from 8 to 
65535. See [KLL Sketch Accuracy and 
Size](https://datasketches.apache.org/docs/KLL/KLLAccuracyAndSize.html).|no, 
defaults to 200|
-|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|
+|`type`|This String should be "KllFloatsSketch" or "KllDoublesSketch"|yes|

Review Comment:
   ```suggestion
   |`type`|Either "KllFloatsSketch" or "KllDoublesSketch"|yes|
   ```



##########
docs/development/extensions-core/datasketches-kll.md:
##########
@@ -50,17 +52,17 @@ The result of the aggregation is a KllFloatsSketch or 
KllDoublesSketch that is t
  }
 ```
 
-|property|description|required?|
+|Property|Description|Required?|
 |--------|-----------|---------|
-|type|This String should be "KllFloatsSketch" or "KllDoublesSketch"|yes|
-|name|A String for the output (result) name of the calculation.|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 from 8 to 
65535. See [KLL Sketch Accuracy and 
Size](https://datasketches.apache.org/docs/KLL/KLLAccuracyAndSize.html).|no, 
defaults to 200|
-|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|
+|`type`|This String should be "KllFloatsSketch" or "KllDoublesSketch"|yes|
+|`name`|A String for the output (result) name of the calculation.|yes|
+|`fieldName`|A String for the name of the input field (can contain sketches or 
raw numeric values).|yes|

Review Comment:
   ```suggestion
   `name`|String representing the output column to store sketch values.|yes|
   ```



##########
docs/development/extensions-core/datasketches-theta.md:
##########
@@ -45,17 +50,18 @@ druid.extensions.loadList=["druid-datasketches"]
  }
 ```
 
-|property|description|required?|
+|Property|Description|Required?|
 |--------|-----------|---------|
-|type|This String should always be "thetaSketch"|yes|
-|name|A String for the output (result) name of the calculation.|yes|
-|fieldName|A String for the name of the aggregator used at ingestion time.|yes|
-|isInputThetaSketch|This should only be used at indexing time if your input 
data contains theta sketch objects. This would be the case if you use 
datasketches library outside of Druid, say with Pig/Hive, to produce the data 
that you are ingesting into Druid |no, defaults to false|
-|size|Must be a power of 2. Internally, size refers to the maximum number of 
entries sketch object will retain. Higher size means higher accuracy but more 
space to store sketches. Note that after you index with a particular size, 
druid will persist sketch in segments and you will use size greater or equal to 
that at query time. See the [DataSketches 
site](https://datasketches.apache.org/docs/Theta/ThetaSize) for details. In 
general, We recommend just sticking to default size. |no, defaults to 16384|
+|`type`|This string should always be "thetaSketch"|yes|
+|`name`|A string for the output (result) name of the calculation.|yes|
+|`fieldName`|A string for the name of the aggregator used at ingestion 
time.|yes|
+|`isInputThetaSketch`|This should only be used at indexing time if your input 
data contains theta sketch objects. This would be the case if you use 
datasketches library outside of Druid, say with Pig/Hive, to produce the data 
that you are ingesting into Druid |no, defaults to false|

Review Comment:
   ```suggestion
   |`isInputThetaSketch`|Only set this to true at indexing time if your input 
data contains theta sketch objects. This applies to cases when you use 
datasketches library outside of Druid, Pig/Hive for hexample, to produce the 
data to ingest into Druid |no, defaults to false|
   ```



##########
docs/development/extensions-core/datasketches-quantiles.md:
##########
@@ -50,17 +52,18 @@ The result of the aggregation is a DoublesSketch that is 
the union of all sketch
  }
 ```
 
-|property|description|required?|
+|Property|Description|Required?|
 |--------|-----------|---------|
-|type|This String should always be "quantilesDoublesSketch"|yes|
-|name|A String for the output (result) name of the calculation.|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|
-|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|
+|`type`|This string should always be "quantilesDoublesSketch"|yes|
+|`name`|A string for the output (result) name of the calculation.|yes|

Review Comment:
   ```suggestion
   `name`|String representing the output column to store sketch values.|yes|
   ```



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