[SPARK-56257][PYTHON][CONNECT] Support DataFrame input for spark.read.json/csv/xml#55057
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Yicong-Huang wants to merge 2 commits intoapache:masterfrom
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[SPARK-56257][PYTHON][CONNECT] Support DataFrame input for spark.read.json/csv/xml#55057Yicong-Huang wants to merge 2 commits intoapache:masterfrom
Yicong-Huang wants to merge 2 commits intoapache:masterfrom
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cc @HyukjinKwon |
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Closing this POC PR. Split into individual PRs per JIRA sub-task under SPARK-55227 |
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What changes were proposed in this pull request?
Allow
spark.read.json(),spark.read.csv(), andspark.read.xml()to accept a DataFrame with a single string column as input. Connect supports JSON and CSV only — XML will be added in a follow-up PR after extending theParseproto.Why are the changes needed?
Parsing in-memory text data into a structured DataFrame currently requires
sc.parallelize(), which is unavailable on Spark Connect. This is the inverse ofDataFrame.toJSON().Does this PR introduce any user-facing change?
Yes.
spark.read.json(),csv(), andxml()now accept a single-string-column DataFrame as input.How was this patch tested?
7 new tests: 4 classic (JSON, JSON+schema, CSV, XML) and 3 Connect (JSON, CSV, XML-unsupported).
Was this patch authored or co-authored using generative AI tooling?
No