Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/17142#discussion_r104105409
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/UnivocityParser.scala
---
@@ -54,39 +54,77 @@ private[csv] class UnivocityParser(
private val dataSchema = StructType(schema.filter(_.name !=
options.columnNameOfCorruptRecord))
- private val valueConverters =
- dataSchema.map(f => makeConverter(f.name, f.dataType, f.nullable,
options)).toArray
-
private val tokenizer = new CsvParser(options.asParserSettings)
private var numMalformedRecords = 0
private val row = new GenericInternalRow(requiredSchema.length)
- // This gets the raw input that is parsed lately.
+ // In `PERMISSIVE` parse mode, we should be able to put the raw
malformed row into the field
+ // specified in `columnNameOfCorruptRecord`. The raw input is retrieved
by this method.
private def getCurrentInput(): String =
tokenizer.getContext.currentParsedContent().stripLineEnd
- // This parser loads an `indexArr._1`-th position value in input tokens,
- // then put the value in `row(indexArr._2)`.
- private val indexArr: Array[(Int, Int)] = {
- val fields = if (options.dropMalformed) {
- // If `dropMalformed` is enabled, then it needs to parse all the
values
- // so that we can decide which row is malformed.
- requiredSchema ++ schema.filterNot(requiredSchema.contains(_))
- } else {
- requiredSchema
- }
- // TODO: Revisit this; we need to clean up code here for readability.
- // See an URL below for related discussions:
- // https://github.com/apache/spark/pull/16928#discussion_r102636720
- val fieldsWithIndexes = fields.zipWithIndex
- corruptFieldIndex.map { case corrFieldIndex =>
- fieldsWithIndexes.filter { case (_, i) => i != corrFieldIndex }
- }.getOrElse {
- fieldsWithIndexes
- }.map { case (f, i) =>
- (dataSchema.indexOf(f), i)
- }.toArray
+ // This parser loads an `tokenIndexArr`-th position value in input
tokens,
+ // then put the value in `row(rowIndexArr)`.
+ //
+ // For example, let's say there is CSV data as below:
+ //
+ // a,b,c
+ // 1,2,A
+ //
+ // Also, let's say `columnNameOfCorruptRecord` is set to "_unparsed",
`header` is `true`
+ // by user and the user selects "c", "b", "_unparsed" and "a" fields. In
this case, we need
+ // to map those values below:
+ //
+ // required schema - ["c", "b", "_unparsed", "a"]
+ // CSV data schema - ["a", "b", "c"]
--- End diff --
ISTM it'd be better to map the names into these variables here,
`reuiqredSchema` and `dataSchema`?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
