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Version: 3.11
Features and pricing

ScalarDB Schema Loader

ScalarDB has its own data model and schema that maps to the implementation-specific data model and schema. In addition, ScalarDB stores internal metadata, such as transaction IDs, record versions, and transaction statuses, to manage transaction logs and statuses when you use the Consensus Commit transaction manager.

Since managing the schema mapping and metadata for transactions can be difficult, you can use ScalarDB Schema Loader, which is a tool to create schemas that doesn't require you to need in-depth knowledge about schema mapping or metadata.

You have two options to specify general CLI options in Schema Loader:

  • Pass the ScalarDB properties file and database-specific or storage-specific options.
  • Pass database-specific or storage-specific options without the ScalarDB properties file. (Deprecated)
note

This tool supports only basic options to create, delete, repair, or alter a table. If you want to use the advanced features of a database, you must alter your tables with a database-specific tool after creating the tables with this tool.

Set up Schema Loader​

Select your preferred method to set up Schema Loader, and follow the instructions.

You can download the release versions of Schema Loader from the ScalarDB Releases page.

Run Schema Loader​

This section explains how to run Schema Loader.

Available commands​

Select how you would like to configure Schema Loader for your database. The preferred method is to use the properties file since other, database-specific methods are deprecated.

The following commands are available when using the properties file:

Usage: java -jar scalardb-schema-loader-<VERSION>.jar [-D] [--coordinator]
       [--no-backup] [--no-scaling] -c=<configPath>
       [--compaction-strategy=<compactionStrategy>] [-f=<schemaFile>]
       [--replication-factor=<replicaFactor>]
       [--replication-strategy=<replicationStrategy>] [--ru=<ru>]
Create/Delete schemas in the storage defined in the config file
  -A, --alter         Alter tables : it will add new columns and create/delete
                        secondary index for existing tables. It compares the
                        provided table schema to the existing schema to decide
                        which columns need to be added and which indexes need
                        to be created or deleted
  -c, --config=<configPath>
                      Path to the config file of ScalarDB
      --compaction-strategy=<compactionStrategy>
                      The compaction strategy, must be LCS, STCS or TWCS
                        (supported in Cassandra)
      --coordinator   Create/delete/repair Coordinator tables
  -D, --delete-all    Delete tables
  -f, --schema-file=<schemaFile>
  -I, --import        Import tables : it will import existing non-ScalarDB
                        tables to ScalarDB.
                      Path to the schema json file
      --no-backup     Disable continuous backup (supported in DynamoDB)
      --no-scaling    Disable auto-scaling (supported in DynamoDB, Cosmos DB)
      --repair-all    Repair tables : it repairs the table metadata of
                               existing tables. When using Cosmos DB, it
                               additionally repairs stored procedure attached
                               to each table
      --replication-factor=<replicaFactor>
                      The replication factor (supported in Cassandra)
      --replication-strategy=<replicationStrategy>
                      The replication strategy, must be SimpleStrategy or
                        NetworkTopologyStrategy (supported in Cassandra)
      --ru=<ru>       Base resource unit (supported in DynamoDB, Cosmos DB)

For a sample properties file, see database.properties.

note

The following database-specific methods have been deprecated. Please use the commands for configuring the properties file instead.

Usage: java -jar scalardb-schema-loader-<VERSION>.jar --jdbc [-D]
      -f=<schemaFile> -j=<url> -p=<password> -u=<user>
Create/Delete JDBC schemas
  -A, --alter         Alter tables : it will add new columns and create/delete
                        secondary index for existing tables. It compares the
                        provided table schema to the existing schema to decide
                        which columns need to be added and which indexes need
                        to be created or deleted
  -D, --delete-all       Delete tables
  -f, --schema-file=<schemaFile>
                        Path to the schema json file
  -j, --jdbc-url=<url>   JDBC URL
  -p, --password=<password>
                        JDBC password
      --repair-all       Repair tables : it repairs the table metadata of
                          existing tables
  -u, --user=<user>      JDBC user

Create namespaces and tables​

To create namespaces and tables by using a properties file, run the following command, replacing the contents in the angle brackets as described:

java -jar scalardb-schema-loader-<VERSION>.jar --config <PATH_TO_SCALARDB_PROPERTIES_FILE> -f <PATH_TO_SCHEMA_FILE> [--coordinator]

If --coordinator is specified, a Coordinator table will be created.

note

The following database-specific CLI arguments have been deprecated. Please use the CLI arguments for configuring the properties file instead.

java -jar scalardb-schema-loader-<VERSION>.jar --jdbc -j <JDBC_URL> -u <USER> -p <PASSWORD> -f <PATH_TO_SCHEMA_FILE>

Alter tables​

You can use a command to add new columns to and create or delete a secondary index for existing tables. This command compares the provided table schema to the existing schema to decide which columns need to be added and which indexes need to be created or deleted.

To add new columns to and create or delete a secondary index for existing tables, run the following command, replacing the contents in the angle brackets as described:

java -jar scalardb-schema-loader-<VERSION>.jar --config <PATH_TO_SCALARDB_PROPERTIES_FILE> -f <PATH_TO_SCHEMA_FILE> --alter
note

The following database-specific CLI arguments have been deprecated. Please use the CLI arguments for configuring the properties file instead.

java -jar scalardb-schema-loader-<VERSION>.jar --jdbc -j <JDBC_URL> -u <USER> -p <PASSWORD> -f <PATH_TO_SCHEMA_FILE> --alter

Delete tables​

You can delete tables by using the properties file. To delete tables, run the following command, replacing the contents in the angle brackets as described:

java -jar scalardb-schema-loader-<VERSION>.jar --config <PATH_TO_SCALARDB_PROPERTIES_FILE> -f <PATH_TO_SCHEMA_FILE> [--coordinator] -D

If --coordinator is specified, the Coordinator table will be deleted as well.

note

The following database-specific CLI arguments have been deprecated. Please use the CLI arguments for configuring the properties file instead.

java -jar scalardb-schema-loader-<VERSION>.jar --jdbc -j <JDBC_URL> -u <USER> -p <PASSWORD> -f <PATH_TO_SCHEMA_FILE> -D

Repair tables​

You can repair the table metadata of existing tables by using the properties file. To repair table metadata of existing tables, run the following command, replacing the contents in the angle brackets as described:

java -jar scalardb-schema-loader-<VERSION>.jar --config <PATH_TO_SCALARDB_PROPERTIES_FILE> -f <PATH_TO_SCHEMA_FILE> [--coordinator] --repair-all
warning

Before executing this command, you should confirm the schema configuration is the same as the one that was last applied.

If --coordinator is specified, the Coordinator table will be repaired as well. In addition, if you're using Cosmos DB for NoSQL, running this command will also repair stored procedures attached to each table.

note

The following database-specific CLI arguments have been deprecated. Please use the CLI arguments for configuring the properties file instead.

java -jar scalardb-schema-loader-<VERSION>.jar --jdbc -j <JDBC_URL> -u <USER> -p <PASSWORD> -f <PATH_TO_SCHEMA_FILE> --repair-all

Import tables​

You can import an existing table in JDBC databases to ScalarDB by using the --import option and an import-specific schema file. For details, see Importing Existing Tables to ScalarDB by Using ScalarDB Schema Loader.

Sample schema file​

The following is a sample schema. For a sample schema file, see schema_sample.json.

{
  "sample_db.sample_table": {
    "transaction": false,
    "partition-key": [
      "c1"
    ],
    "clustering-key": [
      "c4 ASC",
      "c6 DESC"
    ],
    "columns": {
      "c1": "INT",
      "c2": "TEXT",
      "c3": "BLOB",
      "c4": "INT",
      "c5": "BOOLEAN",
      "c6": "INT"
    },
    "secondary-index": [
      "c2",
      "c4"
    ]
  },

  "sample_db.sample_table1": {
    "transaction": true,
    "partition-key": [
      "c1"
    ],
    "clustering-key": [
      "c4"
    ],
    "columns": {
      "c1": "INT",
      "c2": "TEXT",
      "c3": "INT",
      "c4": "INT",
      "c5": "BOOLEAN"
    }
  },

  "sample_db.sample_table2": {
    "transaction": false,
    "partition-key": [
      "c1"
    ],
    "clustering-key": [
      "c4",
      "c3"
    ],
    "columns": {
      "c1": "INT",
      "c2": "TEXT",
      "c3": "INT",
      "c4": "INT",
      "c5": "BOOLEAN"
    }
  }
}

The schema has table definitions that include columns, partition-key, clustering-key, secondary-index, and transaction fields.

  • The columns field defines columns of the table and their data types.
  • The partition-key field defines which columns the partition key is composed of.
  • The clustering-key field defines which columns the clustering key is composed of.
  • The secondary-index field defines which columns are indexed.
  • The transaction field indicates whether the table is for transactions or not.
    • If you set the transaction field to true or don't specify the transaction field, this tool creates a table with transaction metadata if needed.
    • If you set the transaction field to false, this tool creates a table without any transaction metadata (that is, for a table with Storage API).

You can also specify database or storage-specific options in the table definition as follows:

{
  "sample_db.sample_table3": {
    "partition-key": [
      "c1"
    ],
    "columns": {
      "c1": "INT",
      "c2": "TEXT",
      "c3": "BLOB"
    },
    "compaction-strategy": "LCS",
    "ru": 5000
  }
}

The database or storage-specific options you can specify are as follows:

No options are available for JDBC databases.

Scale for performance when using Cosmos DB for NoSQL or DynamoDB​

When using Cosmos DB for NoSQL or DynamoDB, you can scale by using Request Units (RUs) or auto-scaling.

RUs​

You can scale the throughput of Cosmos DB for NoSQL and DynamoDB by specifying the --ru option. When specifying this option, scaling applies to all tables or the ru parameter for each table.

If the --ru option is not set, the default values will be 400 for Cosmos DB for NoSQL and 10 for DynamoDB.

note
  • Schema Loader abstracts Request Units for Cosmos DB for NoSQL and Capacity Units for DynamoDB with RU. Therefore, be sure to set an appropriate value depending on the database implementation.
  • Be aware that Schema Loader sets the same value to both read capacity unit and write capacity unit for DynamoDB.

Auto-scaling​

By default, Schema Loader enables auto-scaling of RUs for all tables: RUs scale between 10 percent and 100 percent of a specified RU depending on the workload. For example, if you specify -r 10000, the RUs of each table auto-scales between 1000 and 10000.

note

Auto-scaling for Cosmos DB for NoSQL is enabled only when this option is set to 4000 or more.

Data-type mapping between ScalarDB and other databases​

The following table shows the supported data types in ScalarDB and their mapping to the data types of other databases.

ScalarDBCassandraCosmos DB for NoSQLDynamoDBMySQLPostgreSQLOracleSQL ServerSQLite
BOOLEANbooleanboolean (JSON)BOOLbooleanbooleannumber(1)bitboolean
INTintnumber (JSON)Nintintintintint
BIGINTbigintnumber (JSON)Nbigintbigintnumber(19)bigintbigint
FLOATfloatnumber (JSON)Ndoublefloatbinary_floatfloat(24)float
DOUBLEdoublenumber (JSON)Ndoubledouble precisionbinary_doublefloatdouble
TEXTtextstring (JSON)Slongtexttextvarchar2(4000)varchar(8000)text
BLOBblobstring (JSON)BlongblobbyteaRAW(2000)varbinary(8000)blob

However, the following data types in JDBC databases are converted differently when they are used as a primary key or a secondary index key. This is due to the limitations of RDB data types.

ScalarDBMySQLPostgreSQLOracle
TEXTVARCHAR(64)VARCHAR(10485760)VARCHAR2(64)
BLOBVARBINARY(64)RAW(64)

The value range of BIGINT in ScalarDB is from -2^53 to 2^53, regardless of the underlying database.

If this data-type mapping doesn't match your application, please alter the tables to change the data types after creating them by using this tool.

Internal metadata for Consensus Commit​

The Consensus Commit transaction manager manages metadata (for example, transaction ID, record version, and transaction status) stored along with the actual records to handle transactions properly.

Thus, along with any columns that the application requires, additional columns for the metadata need to be defined in the schema. Additionally, this tool creates a table with the metadata if you use the Consensus Commit transaction manager.

Use Schema Loader in your application​

You can check the version of Schema Loader from the Maven Central Repository. For example in Gradle, you can add the following dependency to your build.gradle file, replacing <VERSION> with the version of Schema Loader that you want to use:

dependencies {
    implementation 'com.scalar-labs:scalardb-schema-loader:<VERSION>'
}

Create, alter, repair, or delete tables​

You can create, alter, delete, or repair tables that are defined in the schema by using Schema Loader. To do this, you can pass a ScalarDB properties file, schema, and additional options, if needed, as shown below:

public class SchemaLoaderSample {
  public static int main(String... args) throws SchemaLoaderException {
    Path configFilePath = Paths.get("database.properties");
    // "sample_schema.json" and "altered_sample_schema.json" can be found in the "/sample" directory.
    Path schemaFilePath = Paths.get("sample_schema.json");
    Path alteredSchemaFilePath = Paths.get("altered_sample_schema.json");
    boolean createCoordinatorTables = true; // whether to create the Coordinator table or not
    boolean deleteCoordinatorTables = true; // whether to delete the Coordinator table or not
    boolean repairCoordinatorTables = true; // whether to repair the Coordinator table or not

    Map<String, String> tableCreationOptions = new HashMap<>();

    tableCreationOptions.put(
        CassandraAdmin.REPLICATION_STRATEGY, ReplicationStrategy.SIMPLE_STRATEGY.toString());
    tableCreationOptions.put(CassandraAdmin.COMPACTION_STRATEGY, CompactionStrategy.LCS.toString());
    tableCreationOptions.put(CassandraAdmin.REPLICATION_FACTOR, "1");

    tableCreationOptions.put(DynamoAdmin.REQUEST_UNIT, "1");
    tableCreationOptions.put(DynamoAdmin.NO_SCALING, "true");
    tableCreationOptions.put(DynamoAdmin.NO_BACKUP, "true");

    Map<String, String> indexCreationOptions = new HashMap<>();
    indexCreationOptions.put(DynamoAdmin.NO_SCALING, "true");

    Map<String, String> tableReparationOptions = new HashMap<>();
    indexCreationOptions.put(DynamoAdmin.NO_BACKUP, "true");

    // Create tables.
    SchemaLoader.load(configFilePath, schemaFilePath, tableCreationOptions, createCoordinatorTables);

    // Alter tables.
    SchemaLoader.alterTables(configFilePath, alteredSchemaFilePath, indexCreationOptions);

    // Repair tables.
    SchemaLoader.repairTables(configFilePath, schemaFilePath, tableReparationOptions, repairCoordinatorTables);

    // Delete tables.
    SchemaLoader.unload(configFilePath, schemaFilePath, deleteCoordinatorTables);

    return 0;
  }
}

You can also create, delete, or repair a schema by passing a serialized-schema JSON string (the raw text of a schema file) as shown below:

// Create tables.
SchemaLoader.load(configFilePath, serializedSchemaJson, tableCreationOptions, createCoordinatorTables);

// Alter tables.
SchemaLoader.alterTables(configFilePath, serializedAlteredSchemaFilePath, indexCreationOptions);

// Repair tables.
SchemaLoader.repairTables(configFilePath, serializedSchemaJson, tableReparationOptions, repairCoordinatorTables);

// Delete tables.
SchemaLoader.unload(configFilePath, serializedSchemaJson, deleteCoordinatorTables);

When configuring ScalarDB, you can use a Properties object as well, as shown below:

// Create tables.
SchemaLoader.load(properties, serializedSchemaJson, tableCreationOptions, createCoordinatorTables);

// Alter tables.
SchemaLoader.alterTables(properties, serializedAlteredSchemaFilePath, indexCreationOptions);

// Repair tables.
SchemaLoader.repairTables(properties, serializedSchemaJson, tableReparationOptions, repairCoordinatorTables);

// Delete tables.
SchemaLoader.unload(properties, serializedSchemaJson, deleteCoordinatorTables);

Import tables​

You can import an existing JDBC database table to ScalarDB by using the --import option and an import-specific schema file, in a similar manner as shown in Sample schema file. For details, see Importing Existing Tables to ScalarDB by Using ScalarDB Schema Loader.

warning

You should carefully plan to import a table to ScalarDB in production because it will add transaction metadata columns to your database tables and the ScalarDB metadata tables. In this case, there would also be several differences between your database and ScalarDB, as well as some limitations.

The following is an import sample:

public class SchemaLoaderImportSample {
  public static int main(String... args) throws SchemaLoaderException {
    Path configFilePath = Paths.get("database.properties");
    // "import_sample_schema.json" can be found in the "/sample" directory.
    Path schemaFilePath = Paths.get("import_sample_schema.json");
    Map<String, String> tableImportOptions = new HashMap<>();

    // Import tables.
    // You can also use a Properties object instead of configFilePath and a serialized-schema JSON
    // string instead of schemaFilePath.
    SchemaLoader.importTables(configFilePath, schemaFilePath, tableImportOptions);

    return 0;
  }
}