The Apache DolphinScheduler team is pleased to announce the release of Apache DolphinScheduler 1.3.8.
Apache DolphinScheduler is a cloud-native visual Big Data workflow scheduler system. This release comes almost 4 months after the last version. In version 1.3.8, we made many optimizations in Doker & K8s. Docker images has supported multiple architectures, such as arm64, system default parameters optimization and so on. At the same time, related optimizations have been made for some user experience issues. Welcome to pay attention to this version. The key fix of this release is: - the complement date is calculated incorrectly, and the issue [#6007] fixes the bug *Feature* [#5405] [Improvement]Docker & K8s Improvement Plan Round 2 [#5858][Improvement][Docker] Docker image should support multi-arch like arm64 in docker-compose [#5706][Improvement][common] Upgrade the version of fastjson from 1.2.61 to 1.2.75 [#5577][Improvement][UI] Add Project Name in Project Page [#5567][Improvement][UI] Add project id in web ui url for sharing [#5475][Improvement][Api] Upload resource to remote failed, the local tmp file need to be cleared [#5468][Improvement][Net]Optimize IP acquisition in complex network environment [#5467][Improvement][UI] UI cannot be displayed normally in some browsers *BUGFIX* [#6007][Bug][Worker] fix Wrong complement date [#5719][Bug][K8s] Ingress ERROR io.k8s.api.networking.v1beta1.IngressSpec.tls: got "map", expected "array" On TLS enabled [#5701][Bug][UI][DAO]When deleting a user, the accessToken associated with the user should also be deleted [#5699][Bug][UI] Update user error in user information [#5596][Bug][Python] Conflict between python_home and datax_home configuration in dolphinscheduler_env.sh [#5559][Bug][Master Server] Master Server was shutdown but the process still in system [#5581][Bug][Mysql] Specific key was too long, max key length is 767 bytes for varchar(256) in some mysql with innodb_large_prefix=OFF [#5578][Bug][Master] ServerNodeManager WorkerGroupListener capture data change and get data failed [#5570][Bug][Worker] worker.groups in worker.properties is still commented after installation in 1.3.6 [#5550][Bug][Master] remove check with executePath when kill yarn job [#5549][Bug][Worker] SqlTask NPE [#5431][Bug][K8s] Master and worker cannot get the right address with custom DNS in 1.3.6 *Download Links:* https://dolphinscheduler.apache.org/en-us/download/download.html *Release Notes:* https://github.com/apache/dolphinscheduler/releases/tag/1.3.8 Website: https://dolphinscheduler.apache.org/ *DolphinScheduler Resources:* - Issue: https://github.com/apache/dolphinscheduler/issues/ - Mailing list: [email protected] - Documents: https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/quick-start.html - Twitter: @dolphinschedule <https://twitter.com/dolphinschedule> - Slack: https://s.apache.org/dolphinscheduler-slack *About DolphinScheduler:* Apache DolphinScheduler is a cloud-native visual Big Data workflow scheduler system. As a distributed and extensible data workflow scheduler platform with rich directed acyclic graph (DAG) visual interfaces, DolphinScheduler solves complex task dependencies and triggers in the data pipeline. Out-of-the-box, its easy-to-extend processing connects numerous systems to 100,000-level data task scheduling. Apache DolphinScheduler is: - Cloud Native — support multi-cloud/data center workflow management, also supports Kubernetes, Docker deployment and custom task types, distributed scheduling, with overall scheduling capability increased linearly with the scale of the cluster - Support multi-tenant - Highly Reliable — decentralized multi-master and multi-worker, high availability, supported by itself, overload processing - User-Friendly — all process definition operations are visualized, defines key information at a glance, one-click deployment - Supports Rich Scenarios — includes streaming, pause, recover operation, and additional task types such as Spark, Hive, MR, Shell, Python, Flink, Sub_process, and more. Best Regards --------------- Apache DolphinScheduler PMC Chair David Dai [email protected] Linkedin: https://www.linkedin.com/in/dailidong Twitter: @WorkflowEasy <https://twitter.com/WorkflowEasy> ---------------
