Despite the fact that special values such as Inf and NaN are not
supported in standard JSON (they are considered invalid values),
rapidjson does support them. However, it requires the parsing flag
'kParseNanAndInfFlag' to be enabled.
This patch enables the flag to allows JsonParser to parse special
numbers like Inf and NaN. Corresponding modifications have also been
made to JsonSkipper to maintain consistent behavior when zero slots
scans.
Additionally, due to a minor issue in rapidjson v1.1.0 when parsing Inf
and NaN, this patch also updates the rapidjson version to include the
corresponding fix (see https://gerrit.cloudera.org/#/c/21980/).
Testing:
- Added and passed relevant test cases (BE, E2E).
Change-Id: I05ee7c7c7fb7e78fff9570f659ce2d13c94a4e10
Reviewed-on: http://gerrit.cloudera.org:8080/21701
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Prototype of HdfsJsonScanner implemented based on rapidjson, which
supports scanning data from splitting json files.
The scanning of JSON data is mainly completed by two parts working
together. The first part is the JsonParser responsible for parsing the
JSON object, which is implemented based on the SAX-style API of
rapidjson. It reads data from the char stream, parses it, and calls the
corresponding callback function when encountering the corresponding JSON
element. See the comments of the JsonParser class for more details.
The other part is the HdfsJsonScanner, which inherits from HdfsScanner
and provides callback functions for the JsonParser. The callback
functions are responsible for providing data buffers to the Parser and
converting and materializing the Parser's parsing results into RowBatch.
It should be noted that the parser returns numeric values as strings to
the scanner. The scanner uses the TextConverter class to convert the
strings to the desired types, similar to how the HdfsTextScanner works.
This is an advantage compared to using number value provided by
rapidjson directly, as it eliminates concerns about inconsistencies in
converting decimals (e.g. losing precision).
Added a startup flag, enable_json_scanner, to be able to disable this
feature if we hit critical bugs in production.
Limitations
- Multiline json objects are not fully supported yet. It is ok when
each file has only one scan range. However, when a file has multiple
scan ranges, there is a small probability of incomplete scanning of
multiline JSON objects that span ScanRange boundaries (in such cases,
parsing errors may be reported). For more details, please refer to
the comments in the 'multiline_json.test'.
- Compressed JSON files are not supported yet.
- Complex types are not supported yet.
Tests
- Most of the existing end-to-end tests can run on JSON format.
- Add TestQueriesJsonTables in test_queries.py for testing multiline,
malformed, and overflow in JSON.
Change-Id: I31309cb8f2d04722a0508b3f9b8f1532ad49a569
Reviewed-on: http://gerrit.cloudera.org:8080/19699
Reviewed-by: Quanlong Huang <huangquanlong@gmail.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
