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From "Veena Basavaraj (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SQOOP-1771) Investigation CSV IDF FORMAT of the Array/NestedArray/ Set/ Map in Postgres and HIVE.
Date Fri, 21 Nov 2014 22:11:34 GMT

     [ https://issues.apache.org/jira/browse/SQOOP-1771?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Veena Basavaraj updated SQOOP-1771:
    Summary: Investigation CSV IDF FORMAT of the Array/NestedArray/ Set/ Map in Postgres and
HIVE.  (was: Investigation FORMAT of the Array/NestedArray/ Set/ Map in Postgres and HIVE.)

> Investigation CSV IDF FORMAT of the Array/NestedArray/ Set/ Map in Postgres and HIVE.
> -------------------------------------------------------------------------------------
>                 Key: SQOOP-1771
>                 URL: https://issues.apache.org/jira/browse/SQOOP-1771
>             Project: Sqoop
>          Issue Type: Sub-task
>          Components: sqoop2-framework
>            Reporter: Veena Basavaraj
>             Fix For: 1.99.5
> https://cwiki.apache.org/confluence/display/SQOOP/Sqoop2+Intermediate+representation#Sqoop2Intermediaterepresentation-Intermediateformatrepresentationproposal
> The above document does not explicitly say the design goals for choosing the CSV IDF
format for different types but with conversation on of the related tickets  RB : https://reviews.apache.org/r/28139/diff/#.
Here are the considerations.
> Intermediate Data Format is more relevant when we transfer data between the FROM and
TO and both do not agree on the same form of data as it is transferred via sqoop.
> The IDF API as of today exposes 3 types of setter, one for a generic type T, one for
Text/String, one for object array.  
> {code}
>   /**
>    * Set one row of data. If validate is set to true, the data is validated
>    * against the schema.
>    * @param data - A single row of data to be moved.
>    */
>   public void setData(T data) {
>     this.data = data;
>   }
>   /**
>    * Get one row of data.
>    *
>    * @return - One row of data, represented in the internal/native format of
>    *         the intermediate data format implementation.
>    */
>   public T getData() {
>     return data;
>   }
>   /**
>    * Get one row of data as CSV.
>    *
>    * @return - String representing the data in CSV, according to the "FROM" schema.
>    * No schema conversion is done on textData, to keep it as "high performance" option.
>    */
>   public abstract String getTextData();
>   /**
>    * Set one row of data as CSV.
>    *
>    */
>   public abstract void setTextData(String text); 
> /**
>    * Get one row of data as an Object array.
>    *
>    * @return - String representing the data as an Object array
>    * If FROM and TO schema exist, we will use SchemaMatcher to get the data according
to "TO" schema
>    */
>   public abstract Object[] getObjectData();
>   /**
>    * Set one row of data as an Object array.
>    *
>    */
>   public abstract void setObjectData(Object[] data);
>   /**
> {code} 
> NOTE : the java docs are not completely accurate, there is really no validation happening:).
Second CSV in one way the IDF can be represented when it is TEXT.There can be other implementation
of IDF as well such as AVRO or JSON, very similar to the serDe interface in HIVE that allows
custom ways to store data, but in SQOOP it is custom ways to represent data as it flows vis
SQOOP.  Another java doc fix... " String representing the data in CSV, according to the "FROM"
schema.  * No schema conversion is done on textData, to keep it as "high performance" option.",
this also is not accurate. The CSV format is a standard enforced by sqoop implementation,
there is no one STANDARD CSV for all data types esp with nested types.. The FROM schema does
not enforce any standard..
> Anyways, so the design considerations seem to be the following
> 1. the setText/ getText are supposed to allow the FROM and TO to talk the same language
and hence should have very minimal transformations as the data flows through SQOOP. This means
that both FROM and TO agree to give data in the CSV IDF that is standardized in the wiki /
spec/ docs and the read data in the same format. Transformation may have to happen before
the setText() or after the getText, but nothing will happen in between when it flows through
sqoop. If the FROM does a setText and the TO does a getObject then there is time spent it
converting the elements within the CSV string to actual java objects. This means there is
parsing and unescaping / unencoding happening in sqoop.
> 2. The current proposal seems to recommend the formats that are more prominent with the
databases that have been explored in the list, but it is not really a complete set of all
data sources/connectors sqoop may have in future. Most emphasis is on the relational DB stores
since historically sqoop1 only supported that as the FROM source
> https://cwiki.apache.org/confluence/display/SQOOP/Sqoop2+Intermediate+representation#Sqoop2Intermediaterepresentation-Intermediateformatrepresentationproposal
> But overall the goal seem to be more on the side of sql dump and pg dump that use CSV
format and the hope is such transfers in sqoop will happen more.
> 3. Avoiding any CPU cycles, there is no validation that will done to make sure that the
data adheres to the CSV format. It is trust based system that the incoming data will follow
the CSV rules as depicted in the link above 
> https://cwiki.apache.org/confluence/display/SQOOP/Sqoop2+Intermediate+representation#Sqoop2Intermediaterepresentation-Intermediateformatrepresentationproposa
> Next, having know these design goals, the format to encode the nested arrays and maps
can be done in some ways. 
> 2 examples were explored below. HIVE and postgres. Details are given below in comments.
One of the simplest ways was to use the universal JSON jackson api for nested arrays and maps.
> Postgres format  is very similar to that but just needs more hand-rolling instead of
relying on a standard JSON library.  both for arrays and map, this format can be used as a
standard.  Between this and actually using jackson object mapper, the performance differences
are highly unlikely to be different. 
> I would still prefer using a standard JSON library for encoding maps and nested arrays,
so that the connectors can  use the same standard as well.

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