Data in Motion
Data passes through the pipeline in batches. This is how it works:
The origin creates a batch as it reads data from the origin system or as data arrives from the origin system, noting the offset. The offset is the location where the origin stops reading.
The origin sends the batch when the batch is full or when the batch wait time limit elapses. The batch moves through the pipeline from processor to processor until it reaches pipeline destinations.
Destinations write the batch to destination systems, and Data Collector commits the offset internally. Based on the pipeline delivery guarantee, Data Collector either commits the offset as soon as it writes to any destination system or after receiving confirmation of the write from all destination systems.
After the offset commit, the origin stage creates a new batch.
Note that this describes general pipeline behavior. Behavior can differ based on the specific pipeline configuration. For example, for the Kafka Consumer, the offset is stored in Kafka or ZooKeeper. And for origin systems that do not store data, such as Omniture and HTTP Client, offsets are not stored because they aren't relevant.
Single and Multithreaded Pipelines
The information above describes a standard single-threaded pipeline - the origin creates a batch and passes it through the pipeline, creating a new batch only after processing the previous batch.
Some origins can generate multiple threads to enable parallel processing in multithreaded pipelines. In a multithreaded pipeline, you configure the origin to create the number of threads or amount of concurrency that you want to use. And Data Collector creates a number of pipeline runners based on the pipeline Max Runners property to perform pipeline processing. Each thread connects to the origin system and creates a batch of data, and passes the batch to an available pipeline runner.
Each pipeline runner processes one batch at a time, just like a pipeline that runs on a single thread. When the flow of data slows, the pipeline runners wait idly until they are needed, generating an empty batch at regular intervals. You can configure the Runner Idle Time pipeline property specify the interval or to opt out of empty batch generation.
All general references to pipelines in this guide describe single-threaded pipelines, but this information generally applies to multithreaded pipelines. For more details specific to multithreaded pipelines, see Multithreaded Pipeline Overview.
Delivery Guarantee
When you configure a pipeline, you define how you want data to be treated: Do you want to prevent the loss of data or the duplication of data?
- At least once
- Ensures that the pipeline processes all data.
- At most once
- Ensures that data is not processed more than once.
Data Collector Data Types
- BOOLEAN
- BYTE
- BYTE_ARRAY
- CHAR
- DATE
- DATETIME
- DECIMAL
- DOUBLE
- FILE_REF
- FLOAT
- INTEGER
- LIST
- LIST_MAP
- LONG
- MAP
- SHORT
- STRING
- TIME
- ZONED_DATETIME