Description
Issues with current reader behavior.
- `text()` without args returns an empty DF with no columns -> inconsistent, its expected that text will always return a DF with `value` string field,
- `textFile()` without args fails with exception because of the above reason, it expected the DF returned by `text()` to have a `value` field.
- `orc()` does not have var args, inconsistent with others
- `json(single-arg)` was removed, but that caused source compatibility issues -
SPARK-16009 - user specified schema was not respected when text/csv/... were used with no args -
SPARK-16007
The solution I am implementing is to do the following.
1. For each format, there will be a single argument method, and a vararg method. For json, parquet, csv, text, this means adding json(string), etc.. For orc, this means adding orc(varargs).
2. Remove the special handling of text(), csv(), etc. that returns empty dataframe with no fields. Rather pass on the empty sequence of paths to the datasource, and let each datasource handle it right. For e.g, text data source, should return empty DF with schema (value: string)
Attachments
Issue Links
- relates to
-
SPARK-16009 DataFrameRead.json(path) compatibility broken with Spark 1.6
-
- Resolved
-
-
-
- Resolved
-
- links to
