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Releases: Hydrospheredata/mist

v1.1.3

24 Jul 16:36
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Fixed from #547

  • Proper support of file-downloading job status: fix failure handling, up mist-ui to 2.2.1
  • Http API: return error stack traces
  • Fix SQL building for job history
  • MistLib: Fix python test running

v1.1.2

02 Apr 15:50
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  • Added Postgresql support #537, #541 - docs
  • Fixed async interface initialize message sending order - #538

v1.1.1

13 Nov 17:00
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  • Fix mist-worker submittion in cluster deploy mode (#528, #529 )

v1.1.0

08 Nov 20:47
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No changes were made, except adding Spark 2.4.0 and Scala 2.12 support.
2.12 artifacts were published too:

v1.0.0

31 Oct 13:53
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🎉🎉🎉🎉 💯 Released 🎉🎉🎉🎉

After more than half of year from the first release candidate of 1.0.0, Mist finally became stable enough to be released as 1.0.0.
Comparing to the previous RC-18 this release contains only ui related fixes.

v1.0.0-RC17

03 Sep 10:10
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  • Upgrade mist-ui to 2.0.1 (pagination for job list 🔥)
  • Provide full error message from job invocation #501, #508
  • Change default worker settings #513 : workerMode -> exclusive, maxJobs -> 1
  • Mqtt async interface - enable auto reconnect option #510
  • Fix problems with collecting logs from workers #496
  • Http api
    • add DELETE methods for v2/api/functions, v2/api/artifacts, v2/api/contexts #507
    • add startTImeout, performTimeout options for POST v2/api/functions/{id}/jobs
  • Mist-lib
    • add default encoder for List #506
    • handle invalid types error in arguments with default values #497
    • fix encoder for boolean values #492

v1.0.0-RC16

24 May 13:04
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v1.0.0-RC16 Pre-release
Pre-release

This release contains a lot of fixes and improvements around user libraries for functions. New mistlibversion for scala/java isn't compatible with previous versions, so to upgrade a mist to v1.0.0-RC16 it's required to migrate and redeploy functions (migration example)

Python library was completely rewritten and now is called mistpy. Also, now it's available in pipy.
Documentation
Example

  • Python library improvements: #485, #441,
  • Mistlib:
    • Explicit result type declaration in MistFn and Handle was removed. Handle declaration was divided into two parts: first build RawHandle[A] where A is resulting type, then build Handle from it using asHandle/toHandle methods and JsEncoder - fix #440
    • #362 - default main method implementation, now it's possible to run mist functions directly from spark-submit
    • scala:
      • #473 - use default values in case classes for building argument extraction -mist.api.encoding.generic.extractorWithDefaults
    • java:
      • Specific for java JMistFn and JHandle implementations was removed - use mist.api.MistFn and mist.api.Handle
      • #478 - onSparkSession, onSparkSessionWithHive methods into java args
      • #489 :
        • interactions with JsData from java was improved
        • encode resulting value properly - RetVal was removed
  • #491 - fix worker termination
  • #484 - support contexts that were created before v1.0.0-RC15

v1.0.0-RC15

07 May 18:35
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v1.0.0-RC15 Pre-release
Pre-release
  • Manual worker mode fixes:
    • Fix workers.manual.onStop behavior. Previously onStop command was used to invoke user action after stopping worker, now it used directly to stop it (worker expects to handle sigkill and notify master node that it was correctly stopped)
    • Return WORKER_NAME env for onStop - #480
  • Fail not started jobs if a context was marked as broken - #479 , #445
  • Fix spark-submit command building - #472

v1.0.0-RC14

28 Mar 17:31
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v1.0.0-RC14 Pre-release
Pre-release
  • Logs collection improved - now job logs contain logs from spark #435 #462
  • Added support for contexts on kubernetes backed cluster #430 #460
  • Added support for python binary configuration #461 (spark.pyspark.python, spark.pyspark.python.driver)
  • Docker image contains mesos library by default #444 #465
  • Fixed job cancellation #469

v1.0.0-RC13

06 Mar 12:03
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v1.0.0-RC13 Pre-release
Pre-release
  • Minor bug fixes after reworking master-worker communications (#452, #453)
  • Fix streaming jobs cancellation (#454, #328)
  • Fix kafka configuration (#447 )