a2l007 commented on a change in pull request #9449:
URL: https://github.com/apache/druid/pull/9449#discussion_r433524037
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File path: docs/ingestion/native-batch.md
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@@ -1310,6 +1311,56 @@ A spec that applies a filter and reads a subset of the
original datasource's col
This spec above will only return the `page`, `user` dimensions and `added`
metric.
Only rows where `page` = `Druid` will be returned.
+### SQL Input Source
+
+The SQL input source is used to read data directly from RDBMS.
+The SQL input source is _splittable_ and can be used by the [Parallel
task](#parallel-task), where each worker task will read from one SQL query from
the list of queries.
+Since this input source has a fixed input format for reading events, no
`inputFormat` field needs to be specified in the ingestion spec when using this
input source.
+
+|property|description|required?|
+|--------|-----------|---------|
+|type|This should be "sql".|Yes|
+|database|Specifies the database connection details. The database type
corresponds to the extension that supplies the `connectorConfig` support and
this extension must be loaded into Druid. For database types `mysql` and
`postgresql`, the `connectorConfig` support is provided by
[mysql-metadata-storage](../development/extensions-core/mysql.md) and
[postgresql-metadata-storage](../development/extensions-core/postgresql.md)
extensions respectively.|Yes|
+|foldCase|Toggle case folding of database column names. This may be enabled in
cases where the database returns case insensitive column names in query
results.|No|
+|sqls|List of SQL queries where each SQL query would retrieve the data to be
indexed.|Yes|
+
+An example SqlInputSource spec is shown below:
+
+```json
+...
+ "ioConfig": {
+ "type": "index_parallel",
+ "inputSource": {
+ "type": "sql",
+ "database": {
+ "type": "mysql",
+ "connectorConfig": {
+ "connectURI": "jdbc:mysql://host:port/schema",
+ "user": "user",
+ "password": "password"
+ }
+ },
+ "sqls": ["SELECT * FROM table1", "SELECT * FROM table2"]
+ },
+...
+```
+
+The spec above will read all events from two separate SQLs within the interval
`2013-01-01/2013-01-02`.
+Each of the SQL queries will be run in its own sub-task and thus for the above
example, there would be two sub-tasks.
+
+Compared to the other native batch InputSources, SQL InputSource behaves
differently in terms of reading the input data and so it would be helpful to
consider the following points before using this InputSource in a production
environment:
+
+* During indexing, each sub-task would execute one of the SQL queries and the
results are stored locally on disk. The sub-tasks then proceed to read the data
from these local input files and generate segments. Presently, there isn’t any
restriction on the size of the generated files and this would require the
MiddleManagers or Indexers to have sufficient disk capacity based on the volume
of data being indexed.
+
+* Filtering the SQL queries based on the intervals specified in the
`granularitySpec` can avoid unwanted data being retrieved and stored locally by
the indexing sub-tasks.
Review comment:
No, I meant to say that the SQL queries should have date time range
based WHERE clauses with the same interval as the interval specified in the
granularitySpec. If the query doesnt have date time based filters, the query
would be pulling data outside the required intervals, which is unwanted. Hope
it is clear now. I have added an example as well.
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