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Version: 3.13
Features and pricing

How to Migrate Your Applications and Databases into a ScalarDB-Based Environment

This guide describes how to migrate your existing applications and relational databases into ScalarDB-based applications and ScalarDB-managed databases, respectively.

Target audience​

The target audiences for this guide are application developers and database administrators. The purpose of this guide is to help you understand how to migrate your existing applications and databases and in what conditions.

What you will learn​

  • Requirements for the migration
  • Steps to migrate your application
  • Changes to make in your application for the migration

Steps to migrate your application​

  1. Verify the items in the checklist.
  2. Migrate your application (if necessary).
    • ScalarDB provides selection, projection, and join operations with dedicated SQL grammar. Thus, some SQL statements in your application might have to be changed for ScalarDB SQL, for example, at a grammar level or a logic level like aggregation processing.
    • For details, see How to migrate your application.
  3. Back up your database.
    • Although ScalarDB Schema Loader, which you will use to import your database, only changes the metadata of your database when importing it to ScalarDB, you must back it up to avoid unexpected accidents.
    • Follow the administration guide of your database.
  4. Set up a ScalarDB environment.
    • Prepare a configuration file so that ScalarDB can access target databases.
    • For details about ScalarDB configurations, see ScalarDB Configurations.
  5. Import your database to ScalarDB.
    • Prepare an import schema file that defines target schemas and tables. The schemas and tables will be mapped to ScalarDB namespaces and tables, respectively. Note that "schema" is a synonym for "database" in some database systems.
    • Run the ScalarDB Schema Loader with the import option, the ScalarDB configuration file that you created, and the schema file that you prepared.
    • For details on how to use Schema Loader, see Run Schema Loader for importing existing tables.
  6. Switch your application and check the behavior.
    • Now, you can switch your application to the ScalarDB-based application.

Migration checklist​

Before starting the migration, check the following questions. If the answer to any of these questions is "No", you must address them before proceeding with the migration.

How to migrate your application​

Depending on your application environment, you may need to migrate your application in the following three aspects:

  • Change connection settings.
  • Modify SQL statements based on the ScalarDB SQL grammar.
  • Modify application logic if there is no available SQL modification workaround.

Change connection settings​

If your application is based on Java, you can use the ScalarDB JDBC driver when migrating. For details on how to add dependencies for the ScalarDB JDBC driver and rewrite the connection URL, see the ScalarDB JDBC Guide.

If your application is not based on Java, you can connect ScalarDB and issue SQL via gRPC. For details, see ScalarDB Cluster SQL gRPC API Guide.

Modify SQL statements​

You may need to change the SQL statements in your application due to the differences in SQL grammar. Typical examples are as follows. For more details, see ScalarDB SQL Grammar.

  • JOIN queries
    • ScalarDB supports only JOIN queries in the style of writing the table to be joined and the condition in the FROM clause.
    • The JOIN condition and filtering also have a few limitations.
    • You may need to rewrite the queries based on the above. You can choose application-level modification if your SQL queries are not compliant with the ScalarDB specifications.
  • WHERE clause
    • In ScalarDB, predicates must be an OR-wise of AND predicate lists (known as disjunctive normal form or DNF) or an AND-wise of OR predicate lists (known as conjunctive normal form or CNF). Thus, you may have to change the WHERE clause, but note that an arbitrary form of predicates can be changed to either DNF or CNF.
    • Similarly, if you use IN clauses, you will need to change them to either DNF or CNF. For IN clauses with sub-queries, see Modify application logic.
    • ScalarDB adopts a specification similar to that of the LIKE operator and the escape sequence of PostgreSQL and MySQL. If your database is neither PostgreSQL nor MySQL, you may need to change predicates with the LIKE operator.

Modify application logic​

Although ScalarDB SQL does not provide some functionalities, such as aggregate queries and sub-queries, those queries can be modified to application-level implementations. Typical modification techniques are as follows:

  • Aggregate queries
    • For simple aggregate queries such as count() and sum() without the GROUP BY clause, you can use SELECT for the target records and then count the number of records or calculate the sum by using the results.
    • For GROUP BY aggregate queries, first use SELECT for all target records without the GROUP BY clause. Then, put result records into a multi-map data structure while categorizing them based on the columns specified in the GROUP BY clause, which should be used as keys of the multi-map. Finally, aggregate records for each key in the multi-map. For the multi-map, you can use libraries such as Guava.
  • Sub-queries
    • For sub-queries in the IN clause, first use SELECT for the records specified in the sub-queries, then add result values as OR predicates in the WHERE clause.
    • For other sub-queries, basically, you need to use SELECT for the records for each query, then join or filter results records in your application.
  • Read-modify-write by using a single update query
    • UPDATE queries may often have an expression like an increment or a decrement, for example, UPDATE table SET a = a + 1 WHERE .... In ScalarDB, you need to use SELECT for a target record and then set the incremented value as a constant in a single transaction, just like UPDATE table SET a = 5 WHERE ....

Limitations​

Due to the difference in data types, ScalarDB will throw an error when writing data larger than the maximum size of the column in the underlying database, even if the size is acceptable for the ScalarDB data type. Conversely, in a few types, the data in the underlying database may be larger than the maximum size in ScalarDB. For details, see Data-type mapping from JDBC databases to ScalarDB.

References​