# Connecting Oracle Data Warehouse with AWS SCT
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You can use AWS SCT to convert schemas, code objects, and application code from Oracle Data Warehouse to Amazon Redshift or Amazon Redshift and AWS Glue used in combination. 

## Privileges for Oracle Data Warehouse as a source
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The following privileges are required for using Oracle Data Warehouse as a source:
+ connect 
+ select\$1catalog\$1role 
+ select any dictionary 

## Connecting to Oracle Data Warehouse as a source
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Use the following procedure to connect to your Oracle data warehouse source database with the AWS Schema Conversion Tool. 

**To connect to an Oracle Data Warehouse source database**

1. In the AWS Schema Conversion Tool, choose **Add source**. 

1. Choose **Oracle**, then choose **Next**. 

   The **Add source** dialog box appears.

1. For **Connection name**, enter a name for your database. AWS SCT displays this name in the tree in the left panel. 

1. Use database credentials from AWS Secrets Manager or enter them manually:
   + To use database credentials from Secrets Manager, use the following instructions:

     1. For **AWS Secret**, choose the name of the secret.

     1. Choose **Populate** to automatically fill in all values in the database connection dialog box from Secrets Manager.

     For information about using database credentials from Secrets Manager, see [Configuring AWS Secrets Manager in the AWS Schema Conversion Tool](CHAP_UserInterface.SecretsManager.md).
   + To enter the Oracle source data warehouse connection information manually, use the following instructions:  
****    
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/SchemaConversionTool/latest/userguide/CHAP_Source.OracleDW.html)

1. Choose **Test Connection** to verify that AWS SCT can connect to your source database. 

1. Choose **Connect** to connect to your source database.

## Oracle Data Warehouse to Amazon Redshift conversion settings
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To edit Oracle Data Warehouse to Amazon Redshift conversion settings, choose **Settings** in AWS SCT, and then choose **Conversion settings**. From the upper list, choose **Oracle**, and then choose **Oracle – Amazon Redshift**. AWS SCT displays all available settings for Oracle Data Warehouse to Amazon Redshift conversion.

Oracle Data Warehouse to Amazon Redshift conversion settings in AWS SCT include options for the following:
+ To limit the number of comments with action items in the converted code.

  For **Add comments in the converted code for the action items of selected severity and higher**, choose the severity of action items. AWS SCT adds comments in the converted code for action items of the selected severity and higher.

  For example, to minimize the number of comments in your converted code, choose **Errors only**. To include comments for all action items in your converted code, choose **All messages**.
+ To set the maximum number of tables that AWS SCT can apply to your target Amazon Redshift cluster.

  For **The maximum number of tables for the target Amazon Redshift cluster**, choose the number of tables that AWS SCT can apply to your Amazon Redshift cluster.

  Amazon Redshift has quotas that limit the use tables for different cluster node types. If you choose **Auto**, AWS SCT determines the number of tables to apply to your target Amazon Redshift cluster depending on the node type. Optionally, choose the value manually. For more information, see [Quotas and limits in Amazon Redshift](https://docs.aws.amazon.com/redshift/latest/mgmt/amazon-redshift-limits.html) in the *Amazon Redshift Management Guide*.

  AWS SCT converts all your source tables, even if this is more than your Amazon Redshift cluster can store. AWS SCT stores the converted code in your project and doesn't apply it to the target database. If you reach the Amazon Redshift cluster quota for the tables when you apply the converted code, then AWS SCT displays a warning message. Also, AWS SCT applies tables to your target Amazon Redshift cluster until the number of tables reaches the limit.
+ To migrate partitions of the source table to separate tables in Amazon Redshift. To do so, select **Use the UNION ALL view** and enter the maximum number of target tables that AWS SCT can create for a single source table.

  Amazon Redshift doesn't support table partitioning. To emulate this behavior and make queries run faster, AWS SCT can migrate each partition of your source table to a separate table in Amazon Redshift. Then, AWS SCT creates a view that includes data from all these tables.

  AWS SCT automatically determines the number of partitions in your source table. Depending on the type of source table partitioning, this number can exceed the quota for the tables that you can apply to your Amazon Redshift cluster. To avoid reaching this quota, enter the maximum number of target tables that AWS SCT can create for partitions of a single source table. The default option is 368 tables, which represents a partition for 366 days of a year and two tables for `NO RANGE` and `UNKNOWN` partitions.
+ To convert the data type formatting functions such as `TO_CHAR`, `TO_DATE`, and `TO_NUMBER` with datetime format elements that Amazon Redshift doesn't support. By default, AWS SCT uses the extension pack functions to emulate the usage of these unsupported format elements in the converted code.

  The datetime format model in Oracle includes more elements compared to datetime format strings in Amazon Redshift. When your source code includes only datetime format elements that Amazon Redshift supports, you don't need the extension pack functions in the converted code. To avoid using the extension pack functions in the converted code, select **Datetype format elements that you use in the Oracle code are similar to datetime format strings in Amazon Redshift**. In this case, the converted code works faster.

  The numeric format model in Oracle includes more elements compared to numeric format strings in Amazon Redshift. When your source code includes only numeric format elements that Amazon Redshift supports, you don't need the extension pack functions in the converted code. To avoid using the extension pack functions in the converted code, select **Numeric format elements that you use in the Oracle code are similar to numeric format strings in Amazon Redshift**. In this case, the converted code works faster.
+ To convert Oracle `LEAD` and `LAG` analytic functions. By default, AWS SCT raises an action item for each `LEAD` and `LAG` function.

  When your source code doesn't use the default values for offset in these functions, AWS SCT can emulate the usage of these functions with the `NVL` function. To do so, select **Use the NVL function to emulate the behavior of Oracle LEAD and LAG functions**.
+ To emulate the behavior of primary and unique keys in your Amazon Redshift cluster, select **Emulate the behavior of primary and unique keys**.

  Amazon Redshift doesn't enforce unique and primary keys and uses them for informational purposes only. If you use these constraints in your code, then make sure that AWS SCT emulates their behavior in the converted code.
+ To apply compression to Amazon Redshift table columns. To do so, select **Use compression encoding**.

  AWS SCT assigns compression encoding to columns automatically using the default Amazon Redshift algorithm. For more information, see [Compression encodings](https://docs.aws.amazon.com/redshift/latest/dg/c_Compression_encodings.html) in the *Amazon Redshift Database Developer Guide*.

  By default, Amazon Redshift doesn't apply compression to columns that are defined as sort and distribution keys. You can change this behavior and apply compression to these columns. To do so, select **Use compression encoding for KEY columns**. You can select this option only when you select the **Use compression encoding** option.

## Oracle Data Warehouse to Amazon Redshift conversion optimization settings
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To edit Oracle Data Warehouse to Amazon Redshift conversion optimization settings, choose **Settings** in AWS SCT, and then choose **Conversion settings**. From the upper list, choose **Oracle**, and then choose **Oracle – Amazon Redshift**. In the left pane, choose **Optimization strategies**. AWS SCT displays conversion optimization settings for Oracle Data Warehouse to Amazon Redshift conversion.

Oracle Data Warehouse to Amazon Redshift conversion optimization settings in AWS SCT include options for the following:
+ To work with automatic table optimization. To do so, select **Use Amazon Redshift automatic table tuning**.

  Automatic table optimization is a self-tuning process in Amazon Redshift that automatically optimizes the design of tables. For more information, see [Working with automatic table optimization](https://docs.aws.amazon.com/redshift/latest/dg/t_Creating_tables.html) in the *Amazon Redshift Database Developer Guide*.

  To rely only on the automatic table optimization, choose **None** for **Initial key selection strategy**.
+ To choose sort and distribution keys using your strategy.

  You can choose sort and distribution keys using Amazon Redshift metadata, statistical information, or both these options. For **Initial key selection strategy** on the **Optimization strategies** tab, choose one of the following options:
  + Use metadata, ignore statistical information
  + Ignore metadata, use statistical information
  + Use metadata and statistical information

  Depending on the option that you choose, you can select optimization strategies. Then, for each strategy, enter the value (0–100). These values define the weight of each strategy. Using these weight values, AWS SCT defines how each rule influences on the choice of distribution and sort keys. The default values are based on the AWS migration best practices.

  You can define the size of small tables for the **Find small tables** strategy. For **Min table row count** and **Max table row count**, enter the minimum and maximum number of rows in a table to define it as a small table. AWS SCT applies the `ALL` distribution style to small tables. In this case, a copy of the entire table is distributed to every node.
+ To configure strategy details.

  In addition to defining the weight for each optimization strategy, you can configure the optimization settings. To do so, choose **Conversion optimization**. 
  + For **Sort key columns limit**, enter the maximum number of columns in the sort key.
  + For **Skewed threshold value**, enter the percentage (0–100) of a skewed value for a column. AWS SCT excludes columns with the skew value greater than the threshold from the list of candidates for the distribution key. AWS SCT defines the skewed value for a column as the percentage ratio of the number of occurrences of the most common value to the total number of records.
  + For **Top N queries from the query history table**, enter the number (1–100) of the most frequently used queries to analyze.
  + For **Select statistics user**, choose the database user for which you want to analyze the query statistics.

  Also, on the **Optimization strategies** tab, you can define the size of small tables for the **Find small tables** strategy. For **Min table row count** and **Max table row count**, enter the minimum and maximum number of rows in a table to consider it as a small table. AWS SCT applies the `ALL` distribution style to small tables. In this case, a copy of the entire table is distributed to every node.