THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
State
[Progress progress record] :
Proposed time : 2022/03/01
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Completion time : 2022/05/21
[Issueissue] : https://github.com/apache/incubator-linkis/issues/xxxxx
[Emailemail] : At present, you must initiate a discussion in the wechat group [Apache Linkis Community Development group], and the discussion minutes can be sent to the official dev email of linkis
[Releaserelease] : Linkis- linkis 1.1.0
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Document the state by adding a label to the LKIP page with one of “discussion”, “accepted”, “released”, “rejected”.
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[proposer]:
Motivation & Background
At present, Linkis management console does not provide the management entrance of UDF function, and it relies on Scriptis component in DSS to manage UDF function. Therefore, the creation and modification of UDF function need to rely on the external system Scriptis. Second, currently, multiple UDF versions cannot be controlled. Therefore, historical versions of a UDF function cannot be viewed or rolled back. The current UDF function jar packages and script materials are stored on the host of the server. If the server is replaced, the UDF function jar packages and script materials need to be migrated synchronously
Basic concept
Several types of UDF
| Code Block |
|---|
UDF function (requires registration to use) Universal type of UDF function: refers to the UDF function that can be used by both Hive's hql and Spark's sql, generally compiled into a jar package Spark-type UDF function: Spark-specific UDF, registered through scala or python function, can also be used in sql after registration Custom functions (can be used like normal functions in scripts without registration, PythonUDF and ScalaUDF can only be used in Spark engine) python custom functions: functions written based on python scala custom function: function written based on scala Type ID: UDF_JAR = 0; UDF_PY = 1; UDF_SCALA = 2; FUNCTION_PY = 3; FUNCTION_SCALA = 4; |
Expect to achieve goals
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- Ability
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- to
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- add/modify/delete/version
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- control
...
- the
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- Udf
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- function
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- of
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- the
...
- compiled
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- Jar
...
- package
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- through
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- the
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- linkis
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- management
...
- console
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- Ability
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- to
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- add/modify/delete/version
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- control
...
- the
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- written
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- python/scala
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- script
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- custom
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- functions
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- through
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- the
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- linkis
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- console
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- The
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- jar
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- package/script
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- corresponding
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- to
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- the
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- udf
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- function
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- can
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- be
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- persistently
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- stored
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- in
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- BML
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- Administrator
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- users
...
- who
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- can
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- support
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- udf
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- functions
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- can
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- share
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- their
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- personal
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- udf
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- functions
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- with
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- others
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- Can
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- support
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- the
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- classification
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- selection
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- or
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- input
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- of
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- new
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- types
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- when
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- creating
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- personal
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- udf
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- functions
Implementation plan
The
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linkis_ps_udf_version
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table
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needs
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to
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be
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added
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to
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support
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the
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storage
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of
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UDF
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functions
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on
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BML
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and
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the
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storage
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of
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multi-version
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information
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Relying
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on
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the
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existing
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BML
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material
...
management
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service
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of
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linkis,
...
upload
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the
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jar/script
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material
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of
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the
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udf
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function
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to
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the
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hdfs
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file
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system
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managed
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by
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bml.
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When
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using
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udf,
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you
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need
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to
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download
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from
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bml
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to
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the
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local
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directory
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according
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to
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the
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resourceId
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and
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version.
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The
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latest
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version
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(the
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maximum
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version)
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is
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used
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by
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default.
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Things
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to
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Consider
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&
...
Note:
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- The
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- udf
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- function
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- name
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- under
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- the
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- same
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- user
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- cannot
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- be
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- repeated,
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- user_name
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- and
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- udf_name
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- are
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- unique
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- Need
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- to
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- add
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- the
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- classification
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- field
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- of
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- the
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- udf
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- function
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- When
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- modifying
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- udf,
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- you
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- also
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- need
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- to
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- upload
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- the
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- file
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- to
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- bml
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- (resource_id
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- remains
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- unchanged),
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- and
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- add
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- a
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- new
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- version
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- (version+1)
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- to
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- the
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- udf_version
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- table
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- according
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- to
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- the
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- modification
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- information.
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- Modifying
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- the
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- udf
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- function
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- name
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- is
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- not
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- supported.
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- For
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- shared
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- functions,
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- after
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- modification,
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- manually
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- click
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- to
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- publish
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- the
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- udf
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- version,
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- the
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- version
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- will
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- take
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- effect
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- for
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- the
...
- shared
...
- udf
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- user,
...
- and
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- the
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- impact
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- of
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- modifying
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- the
...
- udf
...
- will
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- be
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- controlled.
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- After
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- the
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- verification
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- is
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- correct,
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- the
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- shared
...
- user
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- will
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- take
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- effect
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- and
...
- use
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- If
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- the
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- shared
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- udf
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- is
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- loaded
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- by
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- the
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- user,
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- it
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- cannot
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- be
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- deleted,
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- it
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- can
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- only
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- be
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- expired,
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- and
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- it
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- can
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- be
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- deleted
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- if
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- it
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- is
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- not
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- loaded
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- by
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- the
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- user
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- Personal
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- udf
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- can
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- be
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- deleted,
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- but
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- cannot
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- be
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- expired
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- Administrative
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- users
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- can
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- share
...
- a
...
- user's
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- udf
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- with
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- other
...
- users,
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- provide
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- an
...
- input
...
- box
...
- to
...
- input
...
- the
...
- user
...
- name
...
- to
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- be
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- shared,
...
- If
...
- the
...
- shared
...
- user
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- already
...
- has
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- a
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- udf
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- with
...
- the
...
- same
...
- name,
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- the
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- sharing
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- cannot
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- be
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- successful,
...
- and
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- the
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- prompt
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- is:
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- 'xx
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- user
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- has
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- a
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- UDF
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- with
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- the
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- same
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- name!
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- You
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- can
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- click
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- to
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- roll
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- back
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- to
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- a
...
- certain
...
- version
...
- to
...
- add
...
- a
...
- new
...
- version
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- (version+1,
...
- other
...
- information
...
- is
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- the
...
- same)
...
- by
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- copying
...
- the
...
- information
...
- of
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- the
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- rollback
...
- version
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- in
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- the
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- udf_version
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- table.
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- Will
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- use
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- the
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- latest
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- version
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- next
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- time
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- UDF
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- handover
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- Transfer
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- the
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- UDF
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- to
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- another
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- user:
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- Change
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- the
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- user
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- of
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- the
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- udf
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- to
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- the
...
- target
...
- user,
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- determine
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- whether
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- the
...
- target
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- user
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- has
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- the
...
- category
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- of
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- the
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- udf,
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- create
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- a
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- category
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- for
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- the
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- target
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- user
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- if
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- it
...
- does
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- not
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- exist,
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- and
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- then
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- update
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- the
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- category
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- id
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- of
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- the
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- udf
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- to
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- the
...
- category
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- id
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- of
...
- the
...
- target
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- user.
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- User
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- departure
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- handover
...
- is
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- equivalent
...
- to
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- handing
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- over
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- all
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- udfs
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- of
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- the
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- user
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- to
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- the
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- new
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- user
Changes
| Modification | Detail | |||
|---|---|---|---|---|
| 1 | Modification of maven module | none | ||
| 2 | Modification of HTTP interface | UDF added POST /api/rest_j/v1/udf/add
UDF modification POST /api/rest_j/v1/udf/update
UDF delete POST /api/rest_j/v1/udf/delete/{id}
UDF share POST /api/rest_j/v1/udf/shareUDF
UDF handover POST /api/rest_j/v1/udf/handover
UDF version publish POST /api/rest_j/v1/udf/publish
Version rollback POST /api/rest_j/v1/udf/rollback
View version list GET /api/rest_j/v1/udf/versionList
UDF management page POST /api/rest_j/v1/udf/managerPages (Note: only the udf created by the user can be seen)
UDF shared user list POST /api/rest_j/v1/udf/getSharedUsers
UDF expires POST /api/rest_j/v1/udf/setExpire
UDF view source code POST /api/rest_j/v1/udf/downloadUdf
Get a list of udf users GET /api/rest_j/v1/udf/allUdfUsers
Get the first-level classification of the user's personal function GET /api/rest_j/v1/udf/userDirectory | ||
| 3 | Modification of the client interface | Some new interfaces are added to the UDFClient client class Query udf information by username category and udf type def getUdfInfosByUdfType(userName: String, category: String, udfType: BigInt): ArrayBuffer[UDFInfoVo] Query the list of udf functions based on jar package by user name def getJarUdf(userName: String): ArrayBuffer[UDFInfoVo] Query list of udf functions based on py script by username def getPyUdf(userName: String): ArrayBuffer[UDFInfoVo] Query a list of udf functions based on scala script by username def getScalaUdf(userName: String): ArrayBuffer[UDFInfoVo] Query a list of custom functions based on py script by username def getPyFuncUdf(userName: String): ArrayBuffer[UDFInfoVo] Query a list of custom functions based on scala script by username def getScalaFuncUdf(userName: String): ArrayBuffer[UDFInfoVo] | ||
| 4 | Modification of database table structure |
| ||
| 5 | Modification of configuration item | none | ||
| 6 | Modification Error code | none | ||
| 7 | Modifications for Third Party Dependenciesnone |
Compatibility, Deprecation, and Migration Plan
- What impact (if any) will there be on existing users?
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