Openmldb meetup No.4 meeting minutes

The content of the meeting

OpenMLDB  Community in  2022  year  6  month  25  The fourth session was held on August  meetup, The videos and materials related to the meeting are as follows ：

OpenMLDB PMC core member  Lu Mian , From low cost 、 High performance online and offline consistency feature platform open source solution , Introduce the consistent production level feature platform online and offline  OpenMLDB  And its  v0.5.0  New performance improvements in the new version 、 Cost reduction 、 Flexibility adds three features . Video link ：https://www.zhihu.com/zvideo/1525167543303700480 The data link ：https://pan.baidu.com/s/12Vk0syf-WgqQ1uBAXtTNBw Extraction code ：open

Apache RocketMQ PMC member  ding , A message processing platform tempered by trillions of flood peaks ——Apache RocketMQ  For topic , Help you understand  Apache RocketMQ  High availability architecture and cloud native era  RocketMQ  New challenges . Video link ：https://www.zhihu.com/zvideo/1525170014009634816 The data link ：https://pan.baidu.com/s/1vU8K1CA7D1aUO3-vggEXRw Extraction code ：open

Apache RocketMQ connect contributor  Sunxiaojian , The depth resolution  Apache RocketMQ  Technical principles and application scenarios of , borrow  RocketMQ OpenMLDB Connector  Lead the audience to explore how to base on  RocketMQ  Quickly build a lightweight data flow platform . Video link ：https://www.zhihu.com/zvideo/1525170045735370752 The data link ：https://pan.baidu.com/s/1fJHmiC_-awjKPtkQFvaTYg Extraction code ：open

Discussion and exchange

Q1：

Excuse me,  Scala  Interface in  OpenMLDB  Is it in the follow-up development plan of ？

A1：

Scala  In theory, we can also call our Java SDK To connect .Scala  Native  SDK At present, in our  Roadmap  On , But it has not been specifically promoted . If you are interested in this requirement , Also welcome to join the community to develop with us .

Q2：

OpenMLDB  Support vectorization ？

A2：

at present  OpenMLDB  Mainly structured tabular data , The vector search function is not supported （ There are many excellent open source tools to support this part of the function ）. If you want to store vectorized data , In fact, it can also be converted into tabular form , If you need vectorized data for feature calculation, you can use  OpenMLDB .

Q3：

Excuse me,  OpenMLDB  How to set  lable？ If it is only characteristic calculation , Which model is better for training ？

A3：

OpenMLDB  Provide feature calculation function , But we can't do model training and reasoning , therefore  label  This column is in  OpenMLDB  There is no need for special treatment here , Just keep it and give it to the later model training . There are many options for model training . You can refer to our case , Pick up  LightGBM, Or other models , such as  XGBoost, Sklearn  etc.  .

Q4：

I've just been in touch recently  featurestore  product , Find out  OpenMLDB  and  Feast  Comparison of such open source products , Looks missing  feature view  Metadata management . as well as  feast  This kind of product is to give computing power to other cloud computing ,OpenMLDB  More importantly  sql engine  Computing power . I don't know if the understanding is correct ？

A4：

feature view  The definition of seems to be the same as we use  SQL  Definition  feature  The concept is similar , We use forms  schema,  as well as  SQL  To describe the data source format and  feature  Decimation logic . Of course, this one  Feast  The definition of is more concrete , We will learn this description . Comparison  Feast  We emphasize real-time feature computation , Based on the freshest data , Instead of offline feature calculation and online retrieval .

OpenMLDB  Community

I would like to thank you for your  meetup  Strong support , If you want to know more  OpenMLDB  Or participate in Community Technical Exchanges , Relevant information and interaction can be obtained through the following channels .Github: https://github.com/4paradigm/OpenMLDB Official website ：https://openmldb.ai/Email: [email protected]  WeChat ac group ：