Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Pig Wiki" for change 
notification.

The "Pig070LoadStoreHowTo" page has been changed by PradeepKamath.
http://wiki.apache.org/pig/Pig070LoadStoreHowTo?action=diff&rev1=11&rev2=12

--------------------------------------------------

  = Overview =
  This page describes how to go about writing Load functions and Store 
functions using the API available in Pig 0.7.0.
  
- The main motivation for the changes in Pig 0.7.0 load/store api is to move 
closer to using Hadoop's !InputFormat and !OutputFormat classes. This way pig 
users/developers can create new !LoadFunc and !StoreFunc implementation based 
on existing Hadoop !InputFormat and !OutputFormat classes with minimal code. 
The complexity of reading the data and creating a record will now lie in the 
!InputFormat and likewise on the writing end, the complexity of writing will 
lie in the !OutputFormat. This enables !Pig to easily read/write data in new 
storage formats as and when an Hadoop !InputFormat and !OutputFormat is 
available for them.  
+ The main motivation for the changes in Pig 0.7.0 load/store api is to move 
closer to using Hadoop's !InputFormat and !OutputFormat classes. This way pig 
users/developers can create new !LoadFunc and !StoreFunc implementation based 
on existing Hadoop !InputFormat and !OutputFormat classes with minimal code. 
The complexity of reading the data and creating a record will now lie in the 
!InputFormat and likewise on the writing end, the complexity of writing will 
lie in the !OutputFormat. This enables Pig to easily read/write data in new 
storage formats as and when an Hadoop !InputFormat and !OutputFormat is 
available for them.  
  
  '''A general note applicable to both !LoadFunc and !StoreFunc implementations 
is that the implementation should use the new Hadoop 20 API based classes 
(!InputFormat/OutputFormat and related classes) under the 
org.apache.hadoop.mapreduce package instead of the old org.apache.hadoop.mapred 
package.'''
  
  = How to implement a Loader =
- 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/LoadFunc.java?view=markup
 | LoadFunc]]  abstract class which has the main methods for loading data and 
for most use case it might suffice to extend it. There are 3 other optional 
interfaces which can be implemented to achieve extended functionality:
+ 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/LoadFunc.java?view=markup
 | LoadFunc]]  abstract class has the main methods for loading data and for 
most use cases it would suffice to extend it. There are 3 other optional 
interfaces which can be implemented to achieve extended functionality:
   * 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/LoadMetadata.java?view=markup
 | LoadMetadata]] has methods to deal with metadata - most implementation of 
loaders don't need to implement this unless they interact with some metadata 
system. The getSchema() method in this interface provides a way for loader 
implementations to communicate the schema of the data back to pig. If a loader 
implementation returns data comprised of fields of real types (rather than 
!DataByteArray fields), it should provide the schema describing the data 
returned through the getSchema() method. The other methods are concerned with 
other types of metadata like partition keys and statistics. Implementations can 
return null return values for these methods if they are not applicable for that 
implementation.
-  * 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/LoadPushDown.java?view=markup
 | LoadPushDown]] has methods to push operations from pig runtime into loader 
implementations - currently only projections .i.e the pushProjection() method 
is called by Pig to communicate to the loader what exact fields are required in 
the pig script. The loader implementation can choose to honor the request or 
respond that it will not honor the request and return all fields in the data.If 
a loader implementation is able to efficiently return only required fields, it 
should implement !LoadPushDown to improve query performance.
+  * 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/LoadPushDown.java?view=markup
 | LoadPushDown]] has methods to push operations from pig runtime into loader 
implementations - currently only projections .i.e the pushProjection() method 
is called by Pig to communicate to the loader what exact fields are required in 
the pig script. The loader implementation can choose to honor the request or 
respond that it will not honor the request and return all fields in the data. 
If a loader implementation is able to efficiently return only required fields, 
it should implement !LoadPushDown to improve query performance. (Irrespective 
of whether the implementation can or cannot return only the required fields, if 
the implementation also implements getSchema(), the schema returned in 
getSchema() should be for the entire tuple of data.)
   * 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/LoadCaster.java?view=markup
 | LoadCaster]] has methods to convert byte arrays to specific types. A loader 
implementation should implement this if casts (implicit or explicit) from 
!DataByteArray fields to other types need to be supported.
  
- The !LoadFunc abstract class is the main class to extend to implement a 
loader. The methods which need to be overriden are explained below:
+ The !LoadFunc abstract class is the main class to extend for implementing a 
loader. The methods which need to be overriden are explained below:
   * getInputFormat() :This method will be called by Pig to get the 
!InputFormat used by the loader. The methods in the !InputFormat (and 
underlying !RecordReader) will be called by pig in the same manner (and in the 
same context) as by Hadoop in a map-reduce java program. If the !InputFormat is 
a hadoop packaged one, the implementation should use the new API based one 
under org.apache.hadoop.mapreduce. If it is a custom !InputFormat, it should be 
implemented using the new API in org.apache.hadoop.mapreduce.
-  * setLocation() :This method is called by Pig to communicate the load 
location to the loader. The loader should use this method to communicate the 
same information to the underlying !InputFormat. This method is called multiple 
times by pig - implementations should bear in mind that this method is called 
multiple times and should ensure there are no inconsistent side effects due to 
the multiple calls.
+  * setLocation() :This method is called by Pig to communicate the load 
location to the loader. The loader should use this method to communicate the 
same information to the underlying !InputFormat. This method is called multiple 
times by pig - implementations should bear this in mind and should ensure there 
are no inconsistent side effects due to the multiple calls.
   * prepareToRead() : Through this method the !RecordReader associated with 
the !InputFormat provided by the !LoadFunc is passed to the !LoadFunc. The 
!RecordReader can then be used by the implementation in getNext() to return a 
tuple representing a record of data back to pig.
-  * getNext() :The meaning of getNext() has not changed and is called by Pig 
runtime to get the next tuple in the data - in the new API, this is the method 
wherein the implementation will use the the underlying !RecordReader and 
construct a tuple
+  * getNext() :The meaning of getNext() has not changed and is called by Pig 
runtime to get the next tuple in the data - in this method the implementation 
should use the the underlying !RecordReader and construct the tuple to return.
  
  The following methods have default implementations in !LoadFunc and should be 
overridden only if needed:
   * setUdfContextSignature():This method will be called by Pig both in the 
front end and back end to pass a unique signature to the Loader. The signature 
can be used to store into the UDFContext any information which the Loader needs 
to store between various method invocations in the front end and back end. A 
use case is to store !RequiredFieldList passed to it in 
!LoadPushDown.pushProjection(!RequiredFieldList) for use in the back end before 
returning tuples in getNext(). The default implementation in !LoadFunc has an 
empty body. This method will be called before other methods.
   * relativeToAbsolutePath():Pig runtime will call this method to allow the 
Loader to convert a relative load location to an absolute location. The default 
implementation provided in !LoadFunc handles this for !FileSystem locations. If 
the load source is something else, loader implementation may choose to override 
this.  
  
  == Example Implementation ==
- The loader implementation in the example is a loader for text data with line 
delimiter as '\n' and '\t' as default field delimiter (which can be overridden 
by passing a different field delimiter in the constructor) - this is similar to 
current !PigStorage loader in Pig. The new implementation uses an existing 
Hadoop supported !Inputformat - !TextInputFormat as the underlying !InputFormat.
+ The loader implementation in the example is a loader for text data with line 
delimiter as '\n' and '\t' as default field delimiter (which can be overridden 
by passing a different field delimiter in the constructor) - this is similar to 
current !PigStorage loader in Pig. The implementation uses an existing Hadoop 
supported !Inputformat - !TextInputFormat as the underlying !InputFormat.
  
  {{{
  public class SimpleTextLoader extends LoadFunc {
@@ -143, +143 @@

  }}}
  
  = How to implement a Storer =
- 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/StoreFunc.java?view=markup
 | StoreFunc]]  abstract class has the main methods for storing data and for 
most use case it might suffice to extend it. There is an optional interface 
which can be implemented to achieve extended functionality:
+ 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/StoreFunc.java?view=markup
 | StoreFunc]]  abstract class has the main methods for storing data and for 
most use cases it should suffice to extend it. There is an optional interface 
which can be implemented to achieve extended functionality:
   * 
[[http://svn.apache.org/viewvc/hadoop/pig/trunk/src/org/apache/pig/StoreMetadata.java?view=markup
 | StoreMetadata]]: This interface has methods to interact with metadata 
systems to store schema and store statistics. This interface is truely optional 
and should only be implemented if metadata needs to stored.
  
  The methods which need to be overridden in !StoreFunc are explained below:
-  * getOutputFormat(): This method will be called by Pig to get the 
!OutputFormat used by the storer. The methods in the !OutputFormat (and 
underlying !RecordWriter and !OutputCommitter) will be called by pig in the 
same manner (and in the same context) as by Hadoop in a map-reduce java 
program. If the !OutputFormat is a hadoop packaged one, the implementation 
should use the new API based one in org.apache.hadoop.mapreduce. If it is a 
custom !OutputFormat, it should be implemented using the new API under 
org.apache.hadoop.mapreduce. The checkOutputSpecs() method of the !OutputFormat 
will be called by pig to check the output location up-front. This method will 
also be called as part of the Hadoop call sequence when the job is launched. So 
implementations should ensure that this method can be called multiple times 
without inconsistent side effects. 
+  * getOutputFormat(): This method will be called by Pig to get the 
!OutputFormat used by the storer. The methods in the !OutputFormat (and 
underlying !RecordWriter and !OutputCommitter) will be called by pig in the 
same manner (and in the same context) as by Hadoop in a map-reduce java 
program. If the !OutputFormat is a hadoop packaged one, the implementation 
should use the new API based one under org.apache.hadoop.mapreduce. If it is a 
custom !OutputFormat, it should be implemented using the new API under 
org.apache.hadoop.mapreduce. The checkOutputSpecs() method of the !OutputFormat 
will be called by pig to check the output location up-front. This method will 
also be called as part of the Hadoop call sequence when the job is launched. So 
implementations should ensure that this method can be called multiple times 
without inconsistent side effects. 
   * setStoreLocation(): This method is called by Pig to communicate the store 
location to the storer. The storer should use this method to communicate the 
same information to the underlying !OutputFormat. This method is called 
multiple times by pig - implementations should bear in mind that this method is 
called multiple times and should ensure there are no inconsistent side effects 
due to the multiple calls.  
   * prepareToWrite(): In the new API, writing of the data is through the 
!OutputFormat provided by the !StoreFunc. In prepareToWrite() the !RecordWriter 
associated with the !OutputFormat provided by the !StoreFunc is passed to the 
!StoreFunc. The !RecordWriter can then be used by the implementation in 
putNext() to write a tuple representing a record of data in a manner expected 
by the !RecordWriter.   
-  * putNext(): The meaning of putNext() has not changed and is called by Pig 
runtime to write the next tuple of data - in the new API, this is the method 
wherein the implementation will use the the underlying !RecordWriter to write 
the Tuple outThe meaning of putNext() has not changed and is called by Pig 
runtime to write the next tuple of data - in the new API, this is the method 
wherein the implementation will use the the underlying !RecordWriter to write 
the Tuple out 
+  * putNext(): The meaning of putNext() has not changed and is called by Pig 
runtime to write the next tuple of data - in the new API, this is the method 
wherein the implementation will use the the underlying !RecordWriter to write 
the Tuple out.
  
  The following methods have default implementations in !StoreFunc and should 
be overridden only if necessary:
   * setStoreFunc!UDFContextSignature(): This method will be called by Pig both 
in the front end and back end to pass a unique signature to the Storer. The 
signature can be used to store into the UDFContext any information which the 
Storer needs to store between various method invocations in the front end and 
back end. The default implementation in !StoreFunc has an empty body. This 
method will be called before other methods. 
@@ -158, +158 @@

   * checkSchema(): A Store function should implement this function to check 
that a given schema describing the data to be written is acceptable to it. The 
default implementation in !StoreFunc has an empty body. This method will be 
called before any calls to setStoreLocation(). 
  
  == Example Implementation ==
- The storer implementation in the example is a storer for text data with line 
delimiter as '\n' and '\t' as default field delimiter (which can be overridden 
by passing a different field delimiter in the constructor) - this is similar to 
current !PigStorage storer in Pig. The new implementation uses an existing 
Hadoop supported !OutputFormat - TextOutputFormat as the underlying 
!OutputFormat.
+ The storer implementation in the example is a storer for text data with line 
delimiter as '\n' and '\t' as default field delimiter (which can be overridden 
by passing a different field delimiter in the constructor) - this is similar to 
current !PigStorage storer in Pig. The implementation uses an existing Hadoop 
supported !OutputFormat - TextOutputFormat as the underlying !OutputFormat.
  
  {{{
  public class SimpleTextStorer extends StoreFunc {

Reply via email to