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new ae638e338c docs(msq): update insert vs replace for dimension-based
segment pruning (#13228)
ae638e338c is described below
commit ae638e338c4ec7a7d76eefaff7b4bacbd6fed084
Author: 317brian <[email protected]>
AuthorDate: Thu Nov 3 01:47:44 2022 -0700
docs(msq): update insert vs replace for dimension-based segment pruning
(#13228)
* docs(msq): update insert vs replace to mention dimension-based segment
pruning
* make suggested changes
---
docs/multi-stage-query/concepts.md | 6 +++++-
1 file changed, 5 insertions(+), 1 deletion(-)
diff --git a/docs/multi-stage-query/concepts.md
b/docs/multi-stage-query/concepts.md
index 5955b5fc14..f08d733d7a 100644
--- a/docs/multi-stage-query/concepts.md
+++ b/docs/multi-stage-query/concepts.md
@@ -79,6 +79,8 @@ publishes them at the end of its run. For this reason, it is
best suited to load
INSERT statements to load data in a sequence of microbatches; for that, use
[streaming
ingestion](../ingestion/index.md#streaming) instead.
+When deciding whether to use REPLACE or INSERT, keep in mind that segments
generated with REPLACE can be pruned with dimension-based pruning but those
generated with INSERT cannot. For more information about the requirements for
dimension-based pruning, see [Clustering](#clustering).
+
For more information about the syntax, see [INSERT](./reference.md#insert).
<a name="replace"></a>
@@ -102,6 +104,8 @@ issues](./known-issues.md#select) page.
For more information about the syntax, see [REPLACE](./reference.md#replace).
+When deciding whether to use REPLACE or INSERT, keep in mind that segments
generated with REPLACE can be pruned with dimension-based pruning but those
generated with INSERT cannot. For more information about the requirements for
dimension-based pruning, see [Clustering](#clustering).
+
### Primary timestamp
Druid tables always include a primary timestamp named `__time`.
@@ -159,7 +163,7 @@ To activate dimension-based pruning, these requirements
must be met:
- Segments were generated by a REPLACE statement, not an INSERT statement.
- All CLUSTERED BY columns are single-valued string columns.
-If these requirements are _not_ met, Druid still clusters data during
ingestion, but will not be able to perform
+If these requirements are _not_ met, Druid still clusters data during
ingestion but will not be able to perform
dimension-based segment pruning at query time. You can tell if dimension-based
segment pruning is possible by using the
`sys.segments` table to inspect the `shard_spec` for the segments generated by
an ingestion query. If they are of type
`range` or `single`, then dimension-based segment pruning is possible.
Otherwise, it is not. The shard spec type is also
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