FITS Data Source for Apache Spark
- [01/2018] Launch: project starts!
- [03/2018] Release: version 0.3.0
- [04/2018] Paper:
- [05/2018] Release: version 0.4.0
- [06/2018] New location: spark-fits is an official project of AstroLab!
- [07/2018] Release: version 0.5.0, 0.6.0
- [10/2018] Release: version 0.7.0, 0.7.1
- [12/2018] Release: version 0.7.2
- [03/2019] Release: version 0.7.3
- [05/2019] Release: version 0.8.0, 0.8.1, 0.8.2
- [06/2019] Release: version 0.8.3
- [05/2020] Release: version 0.8.4
- [07/2020] Release: version 0.9.0
- A Spark connector for FITS file.
- A Scala library to manipulate FITS file.
The user interface has been done to be the same as other built-in Spark data sources (CSV, JSON, Avro, Parquet, etc). Note that spark-fits follows Apache Spark Data Source V1 (plan to migrate to V2). See our website for more information. To include spark-fits in your job:
# Scala 2.11 spark-submit --packages "com.github.astrolabsoftware:spark-fits_2.11:0.9.0" <...> # Scala 2.12 spark-submit --packages "com.github.astrolabsoftware:spark-fits_2.12:0.9.0" <...>
or you can link against this library in your program at the following coordinates in your build.sbt
// Scala 2.11 libraryDependencies += "com.github.astrolabsoftware" % "spark-fits_2.11" % "0.9.0" // Scala 2.12 libraryDependencies += "com.github.astrolabsoftware" % "spark-fits_2.12" % "0.9.0"
- Read fits file and organize the HDU data into DataFrames.
- Automatically distribute bintable rows over machines.
- Automatically distribute image rows over machines.
- Automatically infer DataFrame schema from the HDU header.
The header tested so far are very simple, and not so exotic. Over the time, we plan to add many new features based on complex examples (see here). If you use spark-fits, and encounter errors while reading a header, tell us (issues or PR) so that we fix the problem asap!
- Define custom Hadoop InputFile.
- Migrate to Spark DataSource V2