You can see the DML delete statement captured on the AWS DMS dashboard: When you query data using Amazon Athena (later in this post), due to the way AWS DMS adds a column indicating inserts, deletes and updates to the new file created as part of CDC replication, we will not be able to run the Athena query by combining data from both files (initial load and CDC files). Run a simple SELECT statement of employees using the sqldata_employee10 table: Because you’re using standard SQL to query data, you can use JOIN and other SQL syntax to combine data from multiple tables as in the following example: The following is another example that queries unique job titles from the Employee database: As you can see, the query time from Amazon Athena is pretty fast. so we can do more of it. We're Once I resolved issues with the schema I intended to simply rename the table to its final name. the USE TestDB GO ALTER TABLE UserLog DROP CONSTRAINT PK__UserLog__7F8B815172CE9EAE WITH (MOVE … You can apply the same procedure when you are replicating a database from an on-premises instance. I haven't had the opportunity to learn SQL yet. Change the schema of a table: As much as I would love too, time hasn't really allowed me to learn SQL. You can also use it to perform ad hoc analysis and run interactive queries for data that’s stored on Amazon S3. To move all objects in a schema to a different schema, the following steps must be followed. The AWS Glue Data Catalog is accessible throughout your AWS account. On the task tab, choose Table statistics to verify the tables and rows that were replicated to the target database with additional details—in this case, HumanResources data: Next, verify your target Amazon S3 bucket: You can see the HumanResources folder that was created under the dms-replication-mrp bucket. want to copy a table from database A to database B. Athena can analyze structured, unstructured and semi-structured data stored in an S3 bucket. Using sqlserver as the database, create a table using a CREATE TABLE statement, and then choose Run Query: You will create three tables from the HumanResources schema that was replicated by AWS DMS: Employee, Department, and Employee Dept History. Summary Using AWS DMS and Amazon Athena provides a powerful combination. Use the Athena console to run the Create Table The purpose of table A is to record current payroll, and the purpose of table B is to store historical data (for running reports later) Anyway, I need a simple macro that when executed will do the following: 1. I have created a new tablespace PROD_INDX for moving the indexes, so we need to only move indexes as tables will be in originally created tablespace. Be sure to choose the Settings button on the top right to note the staging directory. With respect to how to combine data from both files to run Athena queries to reflect existing and new data inserts is beyond the scope of this blog post. can dataset with Athena. Now that the task is created, verify it on the console. The AWS account that you use for migration should have write and delete access to the Amazon S3 bucket that is used as a target. This solution works for both the types of tablespaces. console that helps you get started creating a table based on data that is stored in Not only can you easily replicate databases to a common data store such as Amazon S3, but you can also query data interactively and run ad hoc queries quickly using ANSI SQL—without needing to set up a target database, aggregate data, or load data into Athena. Azure Data Factory: Click on Create a resource --> Analytics --> Data Factory Fill the mandatory fields and… Creating a replication task Finally, create a replication task to replicate data from source to target. Use the Athena API or CLI to run a SQL query string with DDL Move an existing table to the new Filegroup: If the filegroup you want to move the table to; doesn’t already exist then please create the secondary filegroup and then move the table. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. This post demonstrates an easy way to replicate a SQL Server database that’s hosted on an Amazon EC2 instance to an Amazon S3 storage target. If you've got a moment, please tell us how we can make No data loading or transformation is required, and you can delete table definitions and schema without impacting underlying data in Amazon S3. job! Run the Athena tutorial in the console. On the Scripting Options screen set Script Data to False. Athena uses the AWS Glue Data Catalog to store You can simply create an IAM user policy or bucket policy to provide access to the Amazon S3 bucket so that users can create tables and work with underlying data. and retrieve DATABASE, and DROP TABLE under the hood to create tables and 3. discover data schema and extract, transform, and load (ETL) data. First, you create a database in Athena. Similarly, the target endpoint is your Amazon S3 bucket. The transaction IDs and log sequence numbers stored in the tablespace files also differ between databases. The query is as follows. For more information, see Upgrading to the AWS Glue Data Catalog In order to make sure that the tables will be created in the destination database, click on the Edit Mappings button and make sure that the Create destination table option is ticked, and if any of your tables contain Identity column, make sure to tick the Enable identity insert option, then click the OK button. Wizard. In the File name box on the Export - Access Database dialog box, specify the name of the destination database and then click OK. On the target cluster, to view both the schemas, use the \dt command. browser. The actual CSV file that contains data for each table is in respective folders. However, you can also set up a private VPC endpoint for Amazon S3 that lets you connect the replication instance to Amazon S3 without making it publicly accessible. DBO is a default schema of a SQL Server. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. In addition, AWS Glue lets you automatically On the Athena console, using the Query Editor, type CREATE DATABASE sqlserver, with sqlserver being the name of the database. In Athena, tables and databases are containers for the metadata definitions that define a schema for underlying source data. Regardless of how the tables are created, the tables creation process registers the Move the data from cluster1_table1 to another table in the target database. enabled. You need to define columns that map to source SQL Server data, specify how the data is delimited, and specify the location in Amazon S3 for the source data. databases in the AWS Glue Data Catalog. Select Source Tables and Views wizard will appear on the screen; choose the Tables you wish to transfer from source database to destination database and click Next. That would work, however I am not SQL smart. Data Catalog until you choose to update. language (DDL) statements such as CREATE TABLE, CREATE Tutorial in the console to launch it. This is the location AWS DMS used to replicate SQL Server data in step 1. Table mapping gives you flexibility to migrate specific tables and datasets to a target database and can also be rule-based for datasets that you want to filter when replicating data. Started. Step 2: Use Amazon Athena to run interactive queries for data stored on Amazon S3 There are currently two ways to access Athena: using the AWS Management Console or through a JDBC connection. an Athena-managed internal data catalog that exists side-by-side with the AWS Glue For each dataset, a table needs to exist in Athena. If you want to move your existing table into some other schema, you can try below script. Please refer to your browser's Help pages for instructions. To open index properties, expand the DemoDatabase database >> expand Tables >> expand Indexes. the structure of the data, for example, column names, data types, and the name of With Amazon S3 as a target, data manipulation language (DML) inserts, updates, and deletes are supported with a new file that is created under the same folder for each INSERT statement. we may want to rebuild the table for various reason like fragmentation removal ,moving to different tablespace etc. To be able to use the UNLOAD and COPY commands effectively we need to make use of the Amazon S3 service, create a S3 folder and have an IAMrole with permissions to access Amazon S3. table. To create a table automatically, use an AWS Glue crawler from within Athena. SQL engine. 4 TestDB_3 C:\Database\Data\TestDB_3.ndf 6.937500 (4 row(s) affected) To reclaim the disk space you can shrink the data file [TestDB] using DBCC SHRINKFILE, if that’s why you moved table to another file group. Move data from Table A to Table B. Athena to run queries on the data. In this post, I am sharing a T-SQL script for changing or moving tables between the schema of SQL Server. Find the table from the “Tables” list Click the three dots to the right of the table When you create tables and databases manually, Athena uses HiveQL data definition Another possible approach to move very large table across different schemas ('A' to 'B'), mentioned above is very efficient but this leaves you with partitoned table with a 'dummy' partition in schema 'B' as compared to non partitioned table in schema 'A'.Now what is the most efficient way to convert it to regular table just like in the source. more information about AWS Glue and crawlers, see Integration with AWS Glue. Then use Athena with Glue catalog to query the table. Step-by-Step, Getting For each source table, AWS DMS creates a folder under the specified target folder. Note: To ensure that the tables you have selected will be created in the destination database, click the Edit Mappings button and check the Create Destination Table option. After the database is created, you can create a table based on SQL Server replicated data. the To use the AWS Documentation, Javascript must be DATA_STAGE in queries is the tablespace to be moved and ADURUOZ is the user to which we will move all of its objects. An additional bonus for you to explore is to expand this architecture to use Amazon QuickSight for easy visualization with its built-in integration with Amazon Athena. * , which matches any character zero to … a Prahlad Rao is a solutions architect at Amazon Web Services. This registration occurs in the AWS Glue Data Catalog and enables Right-click on the database name and choose Tasks -> Generate Scripts. One solution to move a table to another filegroup is by dropping the clustered index and using the MOVE TO option as follows. organization using Athena and vice versa. this metadata, using it when you run queries to analyze the underlying Now that we are ready with source data/table and destination table, let's create Azure Data Factory to copy the data. For Your query results are stored in Amazon S3 in the query result location that you table and then issue a query against it using Athena. Databases are simply logical groupings of tables on the lines of catalog and namespace. In the previous post, we discussed how to create Azure SQL Server and Azure SQL Database. Right-click PK_CIDX_Records_ID , as shown in the following image: As I mentioned, once clustered index moves to a secondary filegroup, the table will be moved to the secondary filegroup. Let us now move data between 2 tables with different columns in different databases. The metadata in the table tells Athena where the data is located in Amazon S3, and specifies the structure of the data, for example, column names, data types, and the name of the table. If you needed to clear out the print queue after moving the data, you could run a Delete query after that. Now that source and target databases are being replicated, you can proceed to the second step, which is to configure Amazon Athena to interactively query data on this Amazon S3 bucket. To read about some best practices and tuning tips for Amazon Athena, see this post on the AWS Big Data blog. Click here to return to Amazon Web Services homepage, Replication Instances for AWS Database Migration Service, Using Table Mapping with a Task to Select and Filter Data. Do one of the following: In the Append dialog box, click Current Database, select the destination table from the Table Name combo box, and then click OK.-or-In the Append dialog box, click Another Database. use for obtaining and returning query results.
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