amrishlal commented on a change in pull request #7820:
URL: https://github.com/apache/pinot/pull/7820#discussion_r760591685
##########
File path:
pinot-core/src/test/java/org/apache/pinot/queries/JsonPathQueriesTest.java
##########
@@ -55,17 +60,37 @@
private static final String LONG_COLUMN = "longColumn";
private static final String STRING_COLUMN = "stringColumn";
private static final String JSON_COLUMN = "jsonColumn";
+ private static final String RAW_JSON_COLUMN = "rawJsonColumn";
+ private static final String RAW_BYTES_COLUMN = "rawBytesColumn";
+ private static final String DICTIONARY_BYTES_COLUMN =
"dictionaryBytesColumn";
+ private static final String RAW_STRING_COLUMN = "rawStringColumn";
+ private static final String DICTIONARY_STRING_COLUMN =
"dictionaryStringColumn";
private static final String JSON_COLUMN_WITHOUT_INDEX =
"jsonColumnWithoutIndex";
private static final Schema SCHEMA = new
Schema.SchemaBuilder().setSchemaName(RAW_TABLE_NAME)
.addSingleValueDimension(INT_COLUMN, FieldSpec.DataType.INT)
.addSingleValueDimension(LONG_COLUMN, FieldSpec.DataType.LONG)
.addSingleValueDimension(STRING_COLUMN, FieldSpec.DataType.STRING)
.addSingleValueDimension(JSON_COLUMN, FieldSpec.DataType.JSON)
+ .addSingleValueDimension(RAW_JSON_COLUMN, FieldSpec.DataType.JSON)
+ .addSingleValueDimension(RAW_BYTES_COLUMN, FieldSpec.DataType.BYTES)
Review comment:
@richardstartin This unit test file is only to test JSON path
expressions on `JSON` column. If you are trying to validate JSON_EXTRACT_SCALAR
function, I think a better place for it would be JsonDataTypeQueriesTest.java
which has a lot of test cases for json_extract_scalar. I haven't looked through
the PR in detail, so maybe I am missing something, but will look into more
detail.
@kishoreg Perhaps that was just my own personal impression at the time we
were code reviewing JSON datatype. I suppose it should be ok to allow
`JSON_EXTRACT_SCALAR` to work over `BYTE`, but then there is no guarantee that
`BYTE` or `STRING` would contain JSON data (?), i.e any valid or invalid JSON
data could be put into a `STRING` or `BYTE` column. If those byes or string are
ingested into `JSON` datatype column, then we know for sure that it is valid
JSON and can treat it as such during query processing, indexing, etc.
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