You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@druid.apache.org by GitBox <gi...@apache.org> on 2021/08/12 23:44:36 UTC

[GitHub] [druid] jihoonson commented on a change in pull request #11576: Docs refactor of ingestion. Carries #11541

jihoonson commented on a change in pull request #11576:
URL: https://github.com/apache/druid/pull/11576#discussion_r688147838



##########
File path: docs/ingestion/partitioning.md
##########
@@ -0,0 +1,69 @@
+---
+id: partitioning
+title: Partitioning
+sidebar_label: Partitioning
+description: Describes time chunk and secondary partitioning in Druid. Provides guidance to choose a secondary partition dimension.
+---
+
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one
+  ~ or more contributor license agreements.  See the NOTICE file
+  ~ distributed with this work for additional information
+  ~ regarding copyright ownership.  The ASF licenses this file
+  ~ to you under the Apache License, Version 2.0 (the
+  ~ "License"); you may not use this file except in compliance
+  ~ with the License.  You may obtain a copy of the License at
+  ~
+  ~   http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing,
+  ~ software distributed under the License is distributed on an
+  ~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+  ~ KIND, either express or implied.  See the License for the
+  ~ specific language governing permissions and limitations
+  ~ under the License.
+  -->
+
+You can use segment partitioning and sorting within your Druid datasources to reduce the size of your data and increase performance.
+
+One way to partition is to your load data into separate datasources. This is a perfectly viable approach that works very well when the number of datasources does not lead to excessive per-datasource overheads. 

Review comment:
       ```suggestion
   One way to partition is to load data into separate datasources. This is a perfectly viable approach that works very well when the number of datasources does not lead to excessive per-datasource overheads. 
   ```




-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@druid.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org



---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscribe@druid.apache.org
For additional commands, e-mail: commits-help@druid.apache.org