zhipeng93 commented on code in PR #196:
URL: https://github.com/apache/flink-ml/pull/196#discussion_r1090525929
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flink-ml-lib/src/test/java/org/apache/flink/ml/feature/StandardScalerTest.java:
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@@ -206,7 +206,7 @@ public void testSaveLoadAndPredict() throws Exception {
model = TestUtils.saveAndReload(tEnv, model,
tempFolder.newFolder().getAbsolutePath());
assertEquals(
- Arrays.asList("mean", "std"),
+ Arrays.asList("mean", "std", "version", "timestamp"),
Review Comment:
Well, I think letting `StandardScalerModel` have model version and timestamp
is reasonable, since offline learning could be viewed as a special case of
online learning. What we need to do is to make sure that version and timestamp
has a clear meaning. For example, the version of offline model is always zero
and timestamp is `LONG.MAX_VALUE`.
What do you mean by verify `model data contains those columns`? Do you mean
we only verify `model data` and leave `model version` and `timestamp` unchecked?
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