From 800479d3358d95b4813ea97b93a550c93a2a78bc Mon Sep 17 00:00:00 2001 From: Yuqing Wei Date: Mon, 22 May 2023 20:56:53 -0700 Subject: [PATCH] sparksql source doc --- docs/how-to-guides/sparksql-source-notes.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/docs/how-to-guides/sparksql-source-notes.md b/docs/how-to-guides/sparksql-source-notes.md index f2f43dc7e..4a4cffded 100644 --- a/docs/how-to-guides/sparksql-source-notes.md +++ b/docs/how-to-guides/sparksql-source-notes.md @@ -1,6 +1,6 @@ --- layout: default -title: Storing secrets in Azure Key Vault +title: Using `SparkSQLSource` as Data Source parent: How-to Guides --- @@ -19,7 +19,7 @@ sql_source = SparkSqlSource(name="sparkSqlQuerySource", sql="SELECT * FROM green ``` -1. SparkSQL table +2. SparkSQL table If your source is already defined as a table in Databricks, you can directly use its name as data source in Feathr job. ```python @@ -36,4 +36,6 @@ agg_anchor = FeatureAnchor(name="aggregationFeatures", features=agg_features) ``` -When using SparkSQL table as data source, you need to make sure the table can be accessed by Spark session as the Feathr job. \ No newline at end of file +When using SparkSQL table as data source, you need to make sure the table can be accessed by Spark session as the Feathr job. + +Similarly, tables in Blob storages can also be used as this `SparkSQLSrouce` when using synapse as spark provider.