Migrate From Oracle To Postgres – One of the biggest hurdles facing companies seeking digital transformation is the challenge of migrating from legacy databases. These databases are usually locked away in local data centers, and are expensive to upgrade and difficult to maintain.
We want to make it easier. To that end, we’ve built an open source toolkit that can help you migrate your Oracle databases to Cloud SQL for PostgreSQL, and do so with minimal downtime and friction.
Migrate From Oracle To Postgres
The Oracle to Postgres toolkit uses a combination of existing open source and Google Cloud services, and our own Google tools to simplify the schema transformation process, set up low latency, continuous data redundancy, and ultimately perform Oracle to Cloud SQL migration validation for PostgreSQL.
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Migrations are a multi-step process, and they can be complex and repetitive. We’ve simplified this, creating a detailed process with well-documented, easy-to-implement stages.
Deployment and preparation of resources, where the necessary resources are deployed and connector images are created that will be used during the subsequent phases.
Scheme conversion with Ora2Pg, which is often an iterative process of converting, rebuilding, revising and revising the schema until it best suits your needs.
Datastream ingests data from Oracle by reading the log with LogMiner, then transfers the data to Google Cloud Storage. As new files are being written, a Pub/Sub notification is sent, and files are captured by Dataflow using a custom template to load data into Cloud SQL for PostgreSQL. It allows you to migrate your data in a consistent manner using CDC for low downtime.
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Validate data migration, which can be used to ensure that all data has been migrated correctly and that it is safe to start using the destination database. It can also be used to ensure that downstream objects (such as views or PL/SQL) are compiled correctly.
Since the migration process tends to be iterative, try to migrate a single schedule or schema in a test environment before you get close to production. You can also use the toolkit to migrate partial databases. For example, you can migrate the schema of a specific application, while leaving the rest of the application in Oracle.
This post will guide you through each stage in more detail, detailing the process and considerations we recommend for best results.
Installing the Oracle to Postgres toolkit requires a virtual machine with Docker installed. The virtual machine will be used as a fortress and will require access to Oracle and PostgreSQL databases. This foundation will be used to deploy resources, run Ora2Pg, and run data validation queries.
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The toolkit will publish a number of resources used in the migration process. You will also create several Docker images used to run Dataflow, Datastream, Ora2Pg, and Data Validation.
Before you begin, make sure that the database you want to migrate is compatible with using Datastream.
Migrating your schema can be a complex process and can sometimes involve manual customization to resolve issues that arise from using non-standard Oracle features. Since the process is often iterative, we have divided it into two phases, one to build the required PostgreSQL schema and the second to implement the schema.
The toolkit defines a basic Ora2pg configuration file that you may want to build upon. The features selected by default also comply with the data migration template, in particular with regard to using Oracle’s ROWID function to reliably copy tables to PostgreSQL, and Ora2Pg’s default naming conventions (ie changing all names to lowercase). These options should not be modified if you plan to use the Data Migration Dataflow template, as they are assumed to have been used.
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The Oracle ROWID attribute, which maintains a constant and unique identifier for each row, is used in paging as a default replacement for primary keys, in case the table does not have a primary key. This is required to migrate data using the toolkit, although the field can be removed after the migration is complete if the field is not required by the application. The design converts the Oracle ROWID value into an integer, and then the column is defined as a sequence in PostgreSQL. This allows you to continue using the original ROWID field as the primary key in PostgreSQL even after the migration is complete.
The last stage of the Ora2Pg sample applies the required SQL files created in the previous step to PostgresQL. To run this multiple times during an iteration, be sure to delete previous schema iterations from PostgreSQL before applying again.
Because the Migration Toolkit is intended to support migration of Oracle tables and data to PostgreSQL, it does not convert or create all Oracle objects by default. However, Ora2Pg supports a much wider range of object transformations. In the event that you wish to convert additional objects outside of tables and their data, the connector image can be used to convert any of the supported Ora2Pg types; However, this will likely require varying degrees of manual fixes depending on the complexity of your Oracle database. Please refer to the Ora2Pg documentation for support on these steps.
The data migration phase will require two sources to deploy for replication, Datastream and Dataflow. A DataStream stream is created that pulls the requested data from Oracle, and raw table snapshots (“increments”) will start replicating as soon as the stream starts. All data will be uploaded to the cloud storage, and then replicate from Cloud Storage to PostgreSQL using Dataflow and Oracle’s model to PostgreSQL.
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Datastream LogMiner is used to CDC replicate all changes for Oracle selected tables, automatically aligning variable changes and paddings. The advantage of caching this pipeline’s data to Cloud Storage is that it allows for easy redeployment in case you want to run the migration again, say, if the PostgreSQL schema changes, without having to restart the extensions against Oracle.
Dataflow functionality is customized using a pre-designed, dataflow-aware template to ensure consistent, low-latency redundancy between Oracle and Cloud SQL for PostgreSQL. The template uses Dataflow’s stateful API to persistently detect and enforce command at the primary key’s granularity level. As mentioned above, it uses Oracle ROWID for tables that do not have a primary key, for authoritative replication of all requested tables. This ensures that the template can scale to as many PostgreSQL writers as needed, to maintain low-latency replication at scale, without losing consistent collation. During the initial (“backfilling”) replication, it is a best practice to monitor PostgreSQL resources and consider whether the replication speed is running slower than expected, as this stage in the pipeline has the highest potential for being a bottleneck. The replication speed can be checked using events in a second scale in a Dataflow job.
Note that DDL changes to the source are not supported during the migration runtime, so ensure that your source schema can be stable for the duration of the migration run.
Due to the inherent complexity of heterogeneous migrations, it is highly recommended to use the data validation portion of the toolkit while preparing to complete the migration. This is to ensure data is replicated reliably across all tables, that the PostgreSQL instance is in good shape and ready to convert, and to validate complex views or PL/SQL logic in case you use Ora2Pg to migrate additional Oracle objects out of the tables (albeit beyond the scope of this post).
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We provide validators that are built from the latest version of our open source data validator. The tool allows you to perform a variety of high-value validations, including schema (column type matching), row counting, and more complex joins.
After Datastream reports that complements are complete, an initial validation process can ensure that the tables look correct and that no errors have occurred that lead to data gaps. Later in the migration process, you can create filtered validations or validate a specific subset of data for pre-validation. Note that because this type of validation is performed once replication from source to destination is stopped, it is important that it be triggered faster than provisioning validation to reduce downtime. For this reason, it provides a variety of options to filter or limit the number of validated tables for faster operation, while providing high confidence in the integrity of the migration.
If you rewrite PL/SQL as part of the migration process, we encourage using more complex validation. For example, using “–sum”*” in validation will ensure that values in all numeric columns add up to the same value. You can also aggregate on a key (eg date/timestamp column) to validate slices of tables. This will help In ensuring that the table is not only valid but also accurate after the SQL transformation has occurred.
The last step in the migration is the slices phase, when your application starts using the destination Cloud SQL instance of PostgreSQL as the logging system. Since downtime is preceded by a database crash, it must be scheduled in advance if it can cause downtime. As part of the process of preparing for the cut, it is a best practice to ensure that your application is as well
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