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[SPARK-23448][SQL] Clarify JSON and CSV parser behavior in document #20666

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[SPARK-23448][SQL] Clarify JSON and CSV parser behavior in document #20666

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Clarify JSON and CSV parser behavior.
viirya Feb 24, 2018
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Update other related documents.
viirya Feb 24, 2018
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Address comment.
viirya Feb 26, 2018
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viirya Feb 27, 2018
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viirya Feb 27, 2018
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viirya Feb 27, 2018
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30 changes: 16 additions & 14 deletions python/pyspark/sql/readwriter.py
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Expand Up @@ -209,13 +209,13 @@ def json(self, path, schema=None, primitivesAsString=None, prefersDecimal=None,
:param mode: allows a mode for dealing with corrupt records during parsing. If None is
set, it uses the default value, ``PERMISSIVE``.

* ``PERMISSIVE`` : sets other fields to ``null`` when it meets a corrupted \
record, and puts the malformed string into a field configured by \
``columnNameOfCorruptRecord``. To keep corrupt records, an user can set \
a string type field named ``columnNameOfCorruptRecord`` in an user-defined \
schema. If a schema does not have the field, it drops corrupt records during \
parsing. When inferring a schema, it implicitly adds a \
``columnNameOfCorruptRecord`` field in an output schema.
* ``PERMISSIVE`` : when it meets a corrupted record, puts the malformed string \
into a field configured by ``columnNameOfCorruptRecord``, and sets other \
fields to ``null``. To keep corrupt records, an user can set a string type \
field named ``columnNameOfCorruptRecord`` in an user-defined schema. If a \
schema does not have the field, it drops corrupt records during parsing. \
When inferring a schema, it implicitly adds a ``columnNameOfCorruptRecord`` \
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@HyukjinKwon HyukjinKwon Feb 24, 2018

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I think we should say it implicitly adds ... if a corrupted record is found while we are here? I think it only adds `columnNameOfCorruptRecord` when it meets a corrupted record during schema inference.

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@viirya viirya Feb 26, 2018

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When users set a string type field named columnNameOfCorruptRecord in an user-defined schema, even no corrupted record, I think the field is still added. Or I misread this sentence?

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@HyukjinKwon HyukjinKwon Feb 26, 2018

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Ah I thought this:

When inferring a schema, it implicitly adds a ``columnNameOfCorruptRecord`` field in an output schema.

describes schema inference because it adds columnNameOfCorruptRecord column if malformed record was found during schema inference. I mean ..:

scala> spark.read.json(Seq("""{"a": 1}""", """{"a":""").toDS).printSchema()
root
 |-- _corrupt_record: string (nullable = true)
 |-- a: long (nullable = true)


scala> spark.read.json(Seq("""{"a": 1}""").toDS).printSchema()
root
 |-- a: long (nullable = true)

but yes I think I misread it. Here we describe things mainly about malformed records already.

field in an output schema.
* ``DROPMALFORMED`` : ignores the whole corrupted records.
* ``FAILFAST`` : throws an exception when it meets corrupted records.

Expand Down Expand Up @@ -393,13 +393,15 @@ def csv(self, path, schema=None, sep=None, encoding=None, quote=None, escape=Non
:param mode: allows a mode for dealing with corrupt records during parsing. If None is
set, it uses the default value, ``PERMISSIVE``.

* ``PERMISSIVE`` : sets other fields to ``null`` when it meets a corrupted \
record, and puts the malformed string into a field configured by \
``columnNameOfCorruptRecord``. To keep corrupt records, an user can set \
a string type field named ``columnNameOfCorruptRecord`` in an \
user-defined schema. If a schema does not have the field, it drops corrupt \
records during parsing. When a length of parsed CSV tokens is shorter than \
an expected length of a schema, it sets `null` for extra fields.
* ``PERMISSIVE`` : when it meets a corrupted record, puts the malformed string \
into a field configured by ``columnNameOfCorruptRecord``, and sets other \
fields to ``null``. To keep corrupt records, an user can set a string type \
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@cloud-fan cloud-fan Feb 26, 2018

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we can't say and sets other fields to null, as it's not the case for CSV

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@viirya viirya Feb 27, 2018

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I think this is talking about a corrupted record, not a record with less/more tokens. If CSV parser fails to parse a record, all other fields are set to null.

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@cloud-fan cloud-fan Feb 27, 2018

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ah, I think we need to explain that, for CSV a record with less/more tokens is not a malformed record.

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@viirya viirya Feb 27, 2018

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Ok. Added.

field named ``columnNameOfCorruptRecord`` in an user-defined schema. If a \
schema does not have the field, it drops corrupt records during parsing. \
A record with less/more tokens than schema is not a corrupted record to CSV. \
When it meets a record having fewer tokens than the length of the schema, \
sets ``null`` to extra fields. When the record has more tokens than the \
length of the schema, it drops extra tokens.
* ``DROPMALFORMED`` : ignores the whole corrupted records.
* ``FAILFAST`` : throws an exception when it meets corrupted records.

Expand Down
30 changes: 16 additions & 14 deletions python/pyspark/sql/streaming.py
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Original file line number Diff line number Diff line change
Expand Up @@ -442,13 +442,13 @@ def json(self, path, schema=None, primitivesAsString=None, prefersDecimal=None,
:param mode: allows a mode for dealing with corrupt records during parsing. If None is
set, it uses the default value, ``PERMISSIVE``.

* ``PERMISSIVE`` : sets other fields to ``null`` when it meets a corrupted \
record, and puts the malformed string into a field configured by \
``columnNameOfCorruptRecord``. To keep corrupt records, an user can set \
a string type field named ``columnNameOfCorruptRecord`` in an user-defined \
schema. If a schema does not have the field, it drops corrupt records during \
parsing. When inferring a schema, it implicitly adds a \
``columnNameOfCorruptRecord`` field in an output schema.
* ``PERMISSIVE`` : when it meets a corrupted record, puts the malformed string \
into a field configured by ``columnNameOfCorruptRecord``, and sets other \
fields to ``null``. To keep corrupt records, an user can set a string type \
field named ``columnNameOfCorruptRecord`` in an user-defined schema. If a \
schema does not have the field, it drops corrupt records during parsing. \
When inferring a schema, it implicitly adds a ``columnNameOfCorruptRecord`` \
field in an output schema.
* ``DROPMALFORMED`` : ignores the whole corrupted records.
* ``FAILFAST`` : throws an exception when it meets corrupted records.

Expand Down Expand Up @@ -621,13 +621,15 @@ def csv(self, path, schema=None, sep=None, encoding=None, quote=None, escape=Non
:param mode: allows a mode for dealing with corrupt records during parsing. If None is
set, it uses the default value, ``PERMISSIVE``.

* ``PERMISSIVE`` : sets other fields to ``null`` when it meets a corrupted \
record, and puts the malformed string into a field configured by \
``columnNameOfCorruptRecord``. To keep corrupt records, an user can set \
a string type field named ``columnNameOfCorruptRecord`` in an \
user-defined schema. If a schema does not have the field, it drops corrupt \
records during parsing. When a length of parsed CSV tokens is shorter than \
an expected length of a schema, it sets `null` for extra fields.
* ``PERMISSIVE`` : when it meets a corrupted record, puts the malformed string \
into a field configured by ``columnNameOfCorruptRecord``, and sets other \
fields to ``null``. To keep corrupt records, an user can set a string type \
field named ``columnNameOfCorruptRecord`` in an user-defined schema. If a \
schema does not have the field, it drops corrupt records during parsing. \
A record with less/more tokens than schema is not a corrupted record to CSV. \
When it meets a record having fewer tokens than the length of the schema, \
sets ``null`` to extra fields. When the record has more tokens than the \
length of the schema, it drops extra tokens.
* ``DROPMALFORMED`` : ignores the whole corrupted records.
* ``FAILFAST`` : throws an exception when it meets corrupted records.

Expand Down
3 changes: 3 additions & 0 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JacksonParser.scala
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Expand Up @@ -357,6 +357,9 @@ class JacksonParser(
}
} catch {
case e @ (_: RuntimeException | _: JsonProcessingException) =>
// JSON parser currently doesn't support partial results for corrupted records.
// For such records, all fields other than the field configured by
// `columnNameOfCorruptRecord` are set to `null`.
throw BadRecordException(() => recordLiteral(record), () => None, e)
}
}
Expand Down
22 changes: 12 additions & 10 deletions sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
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Expand Up @@ -345,12 +345,12 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
* <li>`mode` (default `PERMISSIVE`): allows a mode for dealing with corrupt records
* during parsing.
* <ul>
* <li>`PERMISSIVE` : sets other fields to `null` when it meets a corrupted record, and puts
* the malformed string into a field configured by `columnNameOfCorruptRecord`. To keep
* corrupt records, an user can set a string type field named `columnNameOfCorruptRecord`
* in an user-defined schema. If a schema does not have the field, it drops corrupt records
* during parsing. When inferring a schema, it implicitly adds a `columnNameOfCorruptRecord`
* field in an output schema.</li>
* <li>`PERMISSIVE` : when it meets a corrupted record, puts the malformed string into a
* field configured by `columnNameOfCorruptRecord`, and sets other fields to `null`. To
* keep corrupt records, an user can set a string type field named
* `columnNameOfCorruptRecord` in an user-defined schema. If a schema does not have the
* field, it drops corrupt records during parsing. When inferring a schema, it implicitly
* adds a `columnNameOfCorruptRecord` field in an output schema.</li>
* <li>`DROPMALFORMED` : ignores the whole corrupted records.</li>
* <li>`FAILFAST` : throws an exception when it meets corrupted records.</li>
* </ul>
Expand Down Expand Up @@ -550,12 +550,14 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
* <li>`mode` (default `PERMISSIVE`): allows a mode for dealing with corrupt records
* during parsing. It supports the following case-insensitive modes.
* <ul>
* <li>`PERMISSIVE` : sets other fields to `null` when it meets a corrupted record, and puts
* the malformed string into a field configured by `columnNameOfCorruptRecord`. To keep
* <li>`PERMISSIVE` : when it meets a corrupted record, puts the malformed string into a
* field configured by `columnNameOfCorruptRecord`, and sets other fields to `null`. To keep
* corrupt records, an user can set a string type field named `columnNameOfCorruptRecord`
* in an user-defined schema. If a schema does not have the field, it drops corrupt records
* during parsing. When a length of parsed CSV tokens is shorter than an expected length
* of a schema, it sets `null` for extra fields.</li>
* during parsing. A record with less/more tokens than schema is not a corrupted record to
* CSV. When it meets a record having fewer tokens than the length of the schema, sets
* `null` to extra fields. When the record has more tokens than the length of the schema,
* it drops extra tokens.</li>
* <li>`DROPMALFORMED` : ignores the whole corrupted records.</li>
* <li>`FAILFAST` : throws an exception when it meets corrupted records.</li>
* </ul>
Expand Down
5 changes: 5 additions & 0 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/UnivocityParser.scala
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Expand Up @@ -203,6 +203,8 @@ class UnivocityParser(
case _: BadRecordException => None
}
}
// For records with less or more tokens than the schema, tries to return partial results
// if possible.
throw BadRecordException(
() => getCurrentInput,
() => getPartialResult(),
Expand All @@ -218,6 +220,9 @@ class UnivocityParser(
row
} catch {
case NonFatal(e) =>
// For corrupted records with the number of tokens same as the schema,
// CSV reader doesn't support partial results. All fields other than the field
// configured by `columnNameOfCorruptRecord` are set to `null`.
throw BadRecordException(() => getCurrentInput, () => None, e)
}
}
Expand Down
22 changes: 12 additions & 10 deletions sql/core/src/main/scala/org/apache/spark/sql/streaming/DataStreamReader.scala
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Expand Up @@ -236,12 +236,12 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
* <li>`mode` (default `PERMISSIVE`): allows a mode for dealing with corrupt records
* during parsing.
* <ul>
* <li>`PERMISSIVE` : sets other fields to `null` when it meets a corrupted record, and puts
* the malformed string into a field configured by `columnNameOfCorruptRecord`. To keep
* corrupt records, an user can set a string type field named `columnNameOfCorruptRecord`
* in an user-defined schema. If a schema does not have the field, it drops corrupt records
* during parsing. When inferring a schema, it implicitly adds a `columnNameOfCorruptRecord`
* field in an output schema.</li>
* <li>`PERMISSIVE` : when it meets a corrupted record, puts the malformed string into a
* field configured by `columnNameOfCorruptRecord`, and sets other fields to `null`. To
* keep corrupt records, an user can set a string type field named
* `columnNameOfCorruptRecord` in an user-defined schema. If a schema does not have the
* field, it drops corrupt records during parsing. When inferring a schema, it implicitly
* adds a `columnNameOfCorruptRecord` field in an output schema.</li>
* <li>`DROPMALFORMED` : ignores the whole corrupted records.</li>
* <li>`FAILFAST` : throws an exception when it meets corrupted records.</li>
* </ul>
Expand Down Expand Up @@ -316,12 +316,14 @@ final class DataStreamReader private[sql](sparkSession: SparkSession) extends Lo
* <li>`mode` (default `PERMISSIVE`): allows a mode for dealing with corrupt records
* during parsing. It supports the following case-insensitive modes.
* <ul>
* <li>`PERMISSIVE` : sets other fields to `null` when it meets a corrupted record, and puts
* the malformed string into a field configured by `columnNameOfCorruptRecord`. To keep
* <li>`PERMISSIVE` : when it meets a corrupted record, puts the malformed string into a
* field configured by `columnNameOfCorruptRecord`, and sets other fields to `null`. To keep
* corrupt records, an user can set a string type field named `columnNameOfCorruptRecord`
* in an user-defined schema. If a schema does not have the field, it drops corrupt records
* during parsing. When a length of parsed CSV tokens is shorter than an expected length
* of a schema, it sets `null` for extra fields.</li>
* during parsing. A record with less/more tokens than schema is not a corrupted record to
* CSV. When it meets a record having fewer tokens than the length of the schema, sets
* `null` to extra fields. When the record has more tokens than the length of the schema,
* it drops extra tokens.</li>
* <li>`DROPMALFORMED` : ignores the whole corrupted records.</li>
* <li>`FAILFAST` : throws an exception when it meets corrupted records.</li>
* </ul>
Expand Down