Log4j 2.17.1

Upgrades to Bullet Core 1.5.2 and Bullet DSL 1.2.2

Upgrades to using Log4j 2.17.1

Bullet Core 1.5.1 and DSL 1.2.1

This release updates to Bullet Core 1.5.1 and Bullet DSL 1.2.1.

Nested Lateral View Explode and subqueries with Bullet Core 1.5.0

This release updates to Bullet Core 1.5.0 and Bullet DSL 1.2.0.

Core 1.4.4 and DSL 1.1.8

This release updates to using Bullet Core 1.4.4 and Bullet DSL 1.1.8

Core 1.4.2 and DSL 1.1.7

This release updates to using Bullet Core 1.4.2 and Bullet DSL 1.1.7

Bullet Spark now respects the PubSubMessageSerDe settings released in Bullet Core 1.4.0.

Core 1.3.1 and DSL 1.1.6

This release updates to using Bullet Core 1.3.1 and Bullet DSL 1.1.6

This also changes how TypedAvroBulletRecord and UntypedAvroBulletRecords are serialized in Spark. Bullet Spark uses Kryo for serialization and previously would not hook into the Java serialization for the record types above. The record types above used the Java hooks to read and write Avro. With this release, a registrator for Kryo is used to make sure that the underlying record data is serialized using Avro.

First release using Screwdriver

No new changes

First release on Maven Central - Bintray EOL

Core 1.2.2. No new changes

Bullet Core 1.2.1

Updates Bullet Core to 1.2.1 and (all dependencies that use core to the the latest versions that use 1.2.1)

1.0 First Major Release - Spark 3.0, Expressions, no JSON, PubSub changes, DSL!

This release updates Bullet Spark to the major 1.0 release and is intended to be used with other components that are 1.0+. It updates Bullet Core to 1.2.0 and Bullet DSL to 1.0.1.

There are a lot of minor bug fixes and major interface changes. The following highlights the most important changes.

1. This release migrates to the latest and greatest Spark 3.0 and going forward, only Spark 3.0+ will be supported. This artifact should still work in older Spark clusters.
2. Query Parsing and errors related to that no longer happen in Bullet Core and therefore, not in the backend. Only the BQL interface is supported and BQL parsing and error handling is handled at the API layer. It is assumed that all queries entering the backend are valid and executable. There can still be runtime errors associated with the query but they are handled appropriately. The various defaults provided to the backend with respect to queries are now provided to the Web Service instead and handled at the time of BQL query parsing.
3. The PubSub no longer transfers JSON queries and instead sends serialized binary objects for queries.
4. Bullet DSL support has been added to Spark! This lets you plug in data sources and converters to read your data without having to write your own receiver or ETL! You can enable it by setting bullet.spark.dsl.data.producer.enable: true and configuring Bullet DSL using its settings. See Bullet DSL for details. You can also choose to enable or disable the optional deserializer with bullet.spark.dsl.deserializer.enable.