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In simple words, every data source has one thing in common, it is collection of rows and each row is a collection of fields / columns. Most of not all data sources have strict schema that tells what each field type is.

1. Native format - each row in the data source is a native object, for instance in JSONIDF, an entire row and its fields in sqoop will be represented as a JSON object, in AvroIDF, entire row and its fields will be represented as a Avro record
2. CSV text format - each row and its fields are represented as CSV text
3. Object Array format  - each field in the row is an element in the object array. Hence a row in the data source is represented as a object array. 

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NOTE: The CSV text format and the Object Array format are custom and  prescribed by Sqoop and the details of this format for every supported column type in the schema are are described below.

Design goals

There are a few prior documents that depict the design goals, but it is not crystal clear. Refer to this this doc for some context on the research done prior to defining the IDF API. It explains some of the goals of using CSV and Object Array formats. Some of the design influence comes from the its predecessor Sqoop1.Design goals

1. Support data transfer across connectors using an "internal" in memory data representation

2. CSV is a common format in many databases and hence sqoop's design goals primarily want to optimize for such data sources. But it is unclear how much of performance gains does CSV text provide. 
   The following is a java doc comment I pulled from the code that explains the choice of CSV.

    

   Why a "native" internal format and then return CSV text too?
   Imagine a connector that moves data from a system that stores data as a
   serialization format called FooFormat. If I also need the data to be
   written into HDFS as FooFormat, the additional cycles burnt in converting
   the FooFormat to text and back is useless - so using the sqoop specified
   CSV text format saves those extra cycles
   <p/>
   Most fast access mechanisms, like mysqldump or pgsqldump write the data
   out as CSV, and most often the source data is also represented as CSV
   - so having a minimal CSV support is mandated for all IDF, so we can easily read the
   data out as text and write as text.

    

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ARRAY

BINARY

BIT

DATE

DATE_TIME

DECIMAL

ENUM

FIXED_POINT

FLOATING_POINT

MAP

SET

TEXT

TIME

UNKNOWN

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