techdocsmith commented on a change in pull request #11506:
URL: https://github.com/apache/druid/pull/11506#discussion_r694382528
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
+> in your `partitionDimension` is also unequally distributed. Therefore,
avoid imbalance in data layout and
Review comment:
```suggestion
in your `partitionDimension` is also unequally distributed. Therefore, to
avoid imbalance in data layout,
```
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
+> in your `partitionDimension` is also unequally distributed. Therefore,
avoid imbalance in data layout and
+> review the distribution of values in your source data before deciding on a
partitioning strategy.
+
+> In order for segment pruning to be effective and translate into better query
performance, you _must_ use
+> the `partitionDimension` at query time. You can concatenate values from
multiple
Review comment:
```suggestion
the `partitionDimension` at query time. You can concatenate values from
multiple
```
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
+> in your `partitionDimension` is also unequally distributed. Therefore,
avoid imbalance in data layout and
+> review the distribution of values in your source data before deciding on a
partitioning strategy.
+
+> In order for segment pruning to be effective and translate into better query
performance, you _must_ use
+> the `partitionDimension` at query time. You can concatenate values from
multiple
+> dimensions into a new dimension to use as the `partitionDimension`. In this
case, you
Review comment:
```suggestion
dimensions into a new dimension to use as the `partitionDimension`. In this
case, you
```
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
+> in your `partitionDimension` is also unequally distributed. Therefore,
avoid imbalance in data layout and
+> review the distribution of values in your source data before deciding on a
partitioning strategy.
+
+> In order for segment pruning to be effective and translate into better query
performance, you _must_ use
+> the `partitionDimension` at query time. You can concatenate values from
multiple
+> dimensions into a new dimension to use as the `partitionDimension`. In this
case, you
+> must use that new `partitionDimension` dimension in your
Review comment:
```suggestion
must use that new dimension in your native filter `WHERE` clause.
```
I'm not convinced links are doing much work here. (maybe to filters).
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
+> in your `partitionDimension` is also unequally distributed. Therefore,
avoid imbalance in data layout and
+> review the distribution of values in your source data before deciding on a
partitioning strategy.
Review comment:
```suggestion
review the distribution of values in your source data before deciding on a
partitioning strategy.
```
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
Review comment:
```suggestion
When you use this technique to partition your data, segment sizes may be
unequally distributed if the data
```
##########
File path: docs/ingestion/native-batch.md
##########
@@ -369,11 +369,16 @@ Druid currently supports only one partition function.
The Parallel task will use one subtask when you set `maxNumConcurrentSubTasks`
to 1.
-> Be aware that, with this technique, segment sizes could be skewed if your
chosen `partitionDimension` is also skewed in source data.
-
-> While it is technically possible to concatenate multiple dimensions into a
single new dimension
-> that you go on to specify in `partitionDimension`, remember that you _must_
then use this newly concatenated dimension at query time
-> in order for segment pruning to be effective.
+> When using this technique to partition your data, segment sizes may be
unequally distributed if the data
+> in your `partitionDimension` is also unequally distributed. Therefore,
avoid imbalance in data layout and
+> review the distribution of values in your source data before deciding on a
partitioning strategy.
+
+> In order for segment pruning to be effective and translate into better query
performance, you _must_ use
Review comment:
```suggestion
For segment pruning to be effective and translate into better query
performance, you must use
```
we don't use ital for emphasis. "must" is enough emphasis
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