spotify / scio
git clone https://github.com/spotify/scio.git
v0.15.10 · 1mo ago
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A Scala API for Apache Beam and Google Cloud Dataflow.
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LanguageScala
LicenseApache-2.0
Created2015-03-26 (11y ago)
Last pushtoday
Watchers106
OwnerOrganization
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- 2026-10-20 — #21 daily in scala
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GitHub topics
Links
- GitHub: github.com/spotify/scio
- Homepage: https://spotify.github.io/scio
- Releases · Issues · Hacker News mentions
README excerpt
# Scio > Ecclesiastical Latin IPA: /ˈʃi.o/, [ˈʃiː.o], [ˈʃi.i̯o] > Verb: I can, know, understand, have knowledge. Scio is a Scala API for Apache Beam and Google Cloud Dataflow inspired by Apache Spark and Scalding. # Features - Scala API close to that of Spark and Scalding core APIs - Unified batch and streaming programming model - Fully managed service \* - Integration with Google Cloud products: Cloud Storage, BigQuery, Pub/Sub, Datastore, Bigtable - Avro, Cassandra, Elasticsearch, gRPC, JDBC, neo4j, Parquet, Redis, TensorFlow IOs - Interactive mode with Scio REPL - Type safe BigQuery - Integration with Algebird and Breeze - Pipeline orchestration with Scala Futures - Distributed cache \* provided by Google Cloud Dataflow # Quick Start Download and install the Java Development Kit (JDK) version 11 or higher, eg. adoptium or corretto. Install sbt. Use our giter8 template to quickly create a new Scio job repository: `sbt new spotify/scio.g8` Switch to the new repo (default `scio-job`) and build it: [code] Run the included word count example: `target/universal/stage/bin/scio-job --output=wc` List result files and inspect content: [code] # Documentation Getting Started is the best place to start with Scio. If you are new to Apache Beam and distributed data processing, check out the Beam Programming Guide first for a detailed explanation of the Beam programming model and concepts. If you have experience with other Scala data processing libraries, check out this comparison between Scio, Scalding and Spark. Example Scio pipelines and tests can be found under scio-examples. A lot of them are direct ports from Beam's Java examples. See this page for some of them with side-by-side explanation. Also see Big Data Rosetta Code for common data processing code snippets in Scio, Scalding and Spark. - Scio Docs - main documentation site - Scio Scaladocs - current API documentation - Scio Examples - examples with side-by-side explanation # Artifacts Scio includes the following artifacts: - `scio-avro`: add-on for Avro, can also be used standalone - `scio-cassandra*`: add-ons for Cassandra - `scio-core`: core library - `scio-elasticsearch*`: add-ons for Elasticsearch - `scio-extra`: extra utilities for working with collections, Breeze, etc., best effort support - `scio-google-cloud-platform`: add-on for Google Cloud IO's: BigQuery, Bigtable, Pub/Sub, Datastore, Spanner - `scio-grpc`: add-on for gRPC service calls - `scio-jdbc`: add-on for JDBC IO - `scio-managed`: add-on for Beam's managed transforms. Includes Iceberg - `scio-neo4j`: add-on for Neo4J IO - `scio-parquet`: add-on for Parquet - `scio-redis`: add-on for Redis - `scio-repl`: extension of the Scala REPL with Scio specific operations - `scio-smb`: add-on for Sort Merge Bucket operations - `scio-snowflake`: add-on for Snowflake IO - `scio-tensorflow`: add-on for TensorFlow TFRecords IO and prediction - `scio-test`: all following test utilities. Add to your project as a "test" dependency - `scio-tes