[ANNOUNCE] Apache DolphinScheduler 1.3.8 released

[David Dai <li...@apache.org>]

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

FEATURES
[#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: dev@dolphinscheduler.apache.org
- Documents:
https://dolphinscheduler.apache.org/en-us/docs/latest/user_doc/quick-start.html
- Twitter: @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
DolphinScheduler supports 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
DolphinScheduler adopts a decentralized multi-master and multi-worker
architecture design, which naturally supports easy expansion and high
availability (not restricted by a single point of bottleneck), and its
performance increases linearly with the increase of machines

- User-Friendly
all process definition operations are visualized, defines key
information at a glance, one-click deployment

- Supports Rich Scenarios
DolphinScheduler support rich scenarios which 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
lidongdai@apache.org
Linkedin: https://www.linkedin.com/in/dailidong
Twitter: @WorkflowEasy
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