What is spark streaming checkpoint?
Also, what is spark streaming used for?
Spark Streaming is an extension of the core Spark API that allows data engineers and data scientists to process real-time data from various sources including (but not limited to) Kafka, Flume, and Amazon Kinesis. This processed data can be pushed out to file systems, databases, and live dashboards.
Also, how do I stop spark streaming? If all you need is just stop running streaming application, then simplest way is via Spark admin UI (you can find it's URL in the startup logs of Spark master). There is a section in the UI, that shows running streaming applications, and there are tiny (kill) url buttons near each application ID.
Considering this, how does spark process streaming data?
Steps in a Spark Streaming program
- Spark Streaming Context is used for processing the real-time data streams.
- After Spark Streaming context is defined, we specify the input data sources by creating input DStreams.
- Define the computations using the Sparking Streaming Transformations API like map and reduce to DStreams.
Which of the following sources can spark streaming receive data?
Spark Streaming supports data sources such as HDFS directories, TCP sockets, Kafka, Flume, Twitter, etc. Data Streams can be processed with Spark's core APIS, DataFrames SQL, or machine learning APIs, and can be persisted to a filesystem, HDFS, databases, or any data source offering a Hadoop OutputFormat.