{"action":"opened","number":554,"pull_request":{"url":"https://api.github.com/repos/allwefantasy/streamingpro/pulls/554","id":216887901,"node_id":"MDExOlB1bGxSZXF1ZXN0MjE2ODg3OTAx","html_url":"https://github.com/allwefantasy/streamingpro/pull/554","diff_url":"https://github.com/allwefantasy/streamingpro/pull/554.diff","patch_url":"https://github.com/allwefantasy/streamingpro/pull/554.patch","issue_url":"https://api.github.com/repos/allwefantasy/streamingpro/issues/554","number":554,"state":"open","locked":false,"title":"[Enhance] Auto feature generation","user":{"login":"allwefantasy","id":797758,"node_id":"MDQ6VXNlcjc5Nzc1OA==","avatar_url":"https://avatars0.githubusercontent.com/u/797758?v=4","gravatar_id":"","url":"https://api.github.com/users/allwefantasy","html_url":"https://github.com/allwefantasy","followers_url":"https://api.github.com/users/allwefantasy/followers","following_url":"https://api.github.com/users/allwefantasy/following{/other_user}","gists_url":"https://api.github.com/users/allwefantasy/gists{/gist_id}","starred_url":"https://api.github.com/users/allwefantasy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/allwefantasy/subscriptions","organizations_url":"https://api.github.com/users/allwefantasy/orgs","repos_url":"https://api.github.com/users/allwefantasy/repos","events_url":"https://api.github.com/users/allwefantasy/events{/privacy}","received_events_url":"https://api.github.com/users/allwefantasy/received_events","type":"User","site_admin":false},"body":"## What changes were proposed in this pull request?\r\n\r\nwhen compiling with `-Pautoml ` flag , StreamingPro will provide you module AutoFeatureExt to help you \r\nauto-generate feature from dataframe.\r\n\r\nFor now, AutoFeatureExt only supports  model generate and batch predict, this means you can not\r\ndeploy it as API Application which may have <100ms latency.\r\n\r\nTo use the result of  AutoFeatureExt , you should use\r\n\r\n```sql\r\n-- transform data to vector\r\nrun table1 as AutoFeatureExt.`/tmp/model2` where runMode=\"predict\" as table2;\r\n```\r\ninstead of\r\n\r\n```sql\r\n-- this will throws `not support` exception\r\nregister AutoFeatureExt.`/tmp/model2`  as prefict;\r\n```\r\nmore detail please use command:\r\n\r\n> load model.`example` where alg=\"AutoFeatureExt\" as output;\r\n\r\nAutoFeatureExt is only working with Spark 2.2.x, when you use Spark 2.3.x as the runtime, \r\nerror like following will throws:\r\n```\r\nname: AutoFeatureExt class:streaming.dsl.mmlib.algs.SQLAutoFeatureExt\r\n is not compatible with current core version:2.3.x\r\n```\r\n\r\n## How was this patch tested?\r\nUnit Test\r\n\r\n## Spark Core Compatibility\r\n\r\n1. 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