All Versions
Latest Version
Avg Release Cycle
35 days
Latest Release
381 days ago

Changelog History
Page 2

  • v2.8.5 Changes

    • Click a vertex in a visualization to open a context menu for interactive graph navigation.
  • v2.8.4 Changes

    September 16, 2019
    • Popup box improvements: Parameters are full-width. Popups avoid overlapping. Popups reopen at previous position with previous dimensions.
  • v2.8.3 Changes

    August 05, 2019
    • Added new operation: Export to Hive.
  • v2.8.2 Changes

    July 01, 2019
    • Remote API bugfixes
  • v2.8.1 Changes

    June 12, 2019
    • For consistency, project tables such as vertices and edges can be accessed as input.vertices and input.edges now.
    • Bugfixes for HDFS use under Kerberos, and minor fixes and improvements in LynxKite.
  • v2.8.0 Changes

    • Upgraded to Spark 2.4.3.
  • v2.7.0 Changes

    • Removed jars with gpl licenses.
    • 50+ different color maps are now available for vertex and edge coloring, defaulting to Viridis for new visualization boxes.
    • Files can be overwritten by export operations.
    • Bugfixes and performance improvements.
  • v2.6.2 Changes

    • Bugfixes for ecosystem Docker image and LynxKite.
    • You can change the length of the protection period for the newly created data files through the Python API. Data files not older than this protection period are not deleted by the cleaner. (LynxKite.set_cleaner_min_age(days))
    • Ecosystem docker image now includes JupyterLab.
    • LynxKite can be set up to allow normal file access (that is, circumvent its prefix mechanism).
  • v2.6.1 Changes

    • Scheduling of snapshot sequences and workspace sequences is timezone aware in Python API.
    • Added basic integration with Neo4j through the Import Neo4j operation. Allows importing data from either Node or Relationship objects from Neo4j.
  • v2.6.0 Changes

    • Fixed an issue where "Derived" operations could not be run in non-local mode.
    • The Python API now allows running external computations using the @external decorator.
    • Upgraded to Apache Spark 2.3.2.
    • You can change the number of executors used by LynxKite through the Python API. (LynxKite.set_executors())