Licensing options for this format begin with FME Professional Edition.
The DynamoDB Reader/Writer module enables FME to read and write DynamoDB attribute data.
Overview
DynamoDB is a managed NoSQL database service offered by Amazon Web Services.
The DynamoDB reader/writer communicates using HTTP requests managed by the Amazon Web Services Java SDK.
This chapter assumes familiarity with DynamoDB, the attribute types supported, and its indexing mechanisms.
For more information, please visit the DynamoDB home at
http://aws.amazon.com/dynamodb/
Usage Notes
The performance of this format is dependent on the amount of memory allocated to the Java Virtual Machine (JVM). The following environment variables allow you to specify memory available to Java Plugins:
- FME_JVM_MIN_HEAP_SIZE: Initial heap size for initializing the JVM.
- FME_JVM_MAX_HEAP_SIZE: Maximum heap size for initializing the JVM.
Both variables must be set for FME to honor them, and must be multiples of 1024K (for example, 4M and 64M, or 4096K and 32768K).
Note: To pass additional parameters used by FME to the Java Virtual Machine, use the JAVA_TOOL_OPTIONS environment variable.
Reader Overview
FME considers a DynamoDB dataset to be a database containing a collection of tables. The tables must be defined in Workbench before they can be read.
When reading from the DynamoDB database, each table is considered a feature type in FME and each row of a table one feature in FME.
Open the Workbench DynamoDB Reader Parameters to view the table list options.
Writer Overview
The DynamoDB writer module stores attributes into a DynamoDB database. The DynamoDB writer provides the following capabilities:
- Index Creation: The DynamoDB writer can set up and populate indexes as part of the loading process. When creating a table, a partition key index must be specified. One additional column can be indexed using DynamoDB’s sort key index. The DynamoDB writer also supports the creation of a single global or local secondary index.
- Batch Writes: The DynamoDB writer writes in batches of up to 25 items in order to ensure a faster data loading process. The maximum number of items processed in a single batch can be changed using the Batch Size writer parameter.