org.apache.pig.builtin

Class JsonStorage

java.lang.Object

org.apache.pig.StoreFunc

org.apache.pig.builtin.JsonStorage

All Implemented Interfaces:

StoreFuncInterface, StoreMetadata, StoreResources

public class JsonStorage
extends StoreFunc
implements StoreMetadata, StoreResources

A JSON Pig store function. Each Pig tuple is stored on one line (as one value for TextOutputFormat) so that it can be read easily using TextInputFormat. Pig tuples are mapped to JSON objects. Pig bags are mapped to JSON arrays. Pig maps are also mapped to JSON objects. Maps are assumed to be string to string. A schema is stored in a side file to deal with mapping between JSON and Pig types. The schema file share the same format as the one we use in PigStorage.

Field Summary

Fields

Modifier and Type	Field and Description
protected ResourceSchema	schema
protected org.apache.hadoop.mapreduce.RecordWriter	writer

Constructor Summary

Constructors

Constructor and Description
JsonStorage()

Method Summary

Modifier and Type	Method and Description
void	checkSchema(ResourceSchema s) Set the schema for data to be stored.
ResourceSchema	fixSchema(ResourceSchema s)
java.util.List<java.lang.String>	getCacheFiles() Allow a StoreFunc to specify a list of files it would like placed in the distributed cache.
org.apache.hadoop.mapreduce.OutputFormat	getOutputFormat() Return the OutputFormat associated with StoreFunc.
java.util.List<java.lang.String>	getShipFiles() Allow a StoreFunc to specify a list of files located locally and would like to ship to backend (through distributed cache).
void	prepareToWrite(org.apache.hadoop.mapreduce.RecordWriter writer) Initialize StoreFunc to write data.
void	putNext(Tuple t) Write a tuple to the data store.
void	setStoreFuncUDFContextSignature(java.lang.String signature) This method will be called by Pig both in the front end and back end to pass a unique signature to the StoreFunc which it can use to store information in the UDFContext which it needs to store between various method invocations in the front end and back end.
void	setStoreLocation(java.lang.String location, org.apache.hadoop.mapreduce.Job job) Communicate to the storer the location where the data needs to be stored.
void	storeSchema(ResourceSchema schema, java.lang.String location, org.apache.hadoop.mapreduce.Job job) Store schema of the data being written
void	storeStatistics(ResourceStatistics stats, java.lang.String location, org.apache.hadoop.mapreduce.Job job) Store statistics about the data being written.
java.lang.Boolean	supportsParallelWriteToStoreLocation() DAG execution engines like Tez support optimizing union by writing to output location in parallel from tasks of different vertices.

Methods inherited from class org.apache.pig.StoreFunc

cleanupOnFailure, cleanupOnFailureImpl, cleanupOnSuccess, relToAbsPathForStoreLocation, warn

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.pig.StoreFuncInterface

addCredentials

Field Detail

writer

protected org.apache.hadoop.mapreduce.RecordWriter writer

schema

protected ResourceSchema schema

Constructor Detail

JsonStorage

public JsonStorage()

Method Detail

getOutputFormat

public org.apache.hadoop.mapreduce.OutputFormat getOutputFormat()
                                                         throws java.io.IOException

Description copied from class: StoreFunc

Return the OutputFormat associated with StoreFunc. This will be called on the front end during planning and on the backend during execution.

Specified by:

getOutputFormat in interface StoreFuncInterface

Specified by:

getOutputFormat in class StoreFunc

Returns:

the OutputFormat associated with StoreFunc

Throws:

java.io.IOException - if an exception occurs while constructing the OutputFormat

setStoreLocation

public void setStoreLocation(java.lang.String location,
                             org.apache.hadoop.mapreduce.Job job)
                      throws java.io.IOException

Description copied from class: StoreFunc

Communicate to the storer the location where the data needs to be stored. The location string passed to the StoreFunc here is the return value of StoreFunc.relToAbsPathForStoreLocation(String, Path) This method will be called in the frontend and backend multiple times. 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. StoreFunc.checkSchema(ResourceSchema) will be called before any call to StoreFunc.setStoreLocation(String, Job).

Specified by:

setStoreLocation in interface StoreFuncInterface

Specified by:

setStoreLocation in class StoreFunc

Parameters:

location - Location returned by StoreFunc.relToAbsPathForStoreLocation(String, Path)

job - The Job object

Throws:

java.io.IOException - if the location is not valid.

setStoreFuncUDFContextSignature

public void setStoreFuncUDFContextSignature(java.lang.String signature)

Description copied from class: StoreFunc

This method will be called by Pig both in the front end and back end to pass a unique signature to the StoreFunc which it can use to store information in the UDFContext which it needs to store between various method invocations in the front end and back end. This method will be called before other methods in StoreFunc. This is necessary because in a Pig Latin script with multiple stores, the different instances of store functions need to be able to find their (and only their) data in the UDFContext object. The default implementation is a no-op.

Specified by:

setStoreFuncUDFContextSignature in interface StoreFuncInterface

Overrides:

setStoreFuncUDFContextSignature in class StoreFunc

Parameters:

signature - a unique signature to identify this StoreFunc

checkSchema

public void checkSchema(ResourceSchema s)
                 throws java.io.IOException

Description copied from class: StoreFunc

Set the schema for data to be stored. This will be called on the front end during planning if the store is associated with a schema. A Store function should implement this function to check that a given schema is acceptable to it. For example, it can check that the correct partition keys are included; a storage function to be written directly to an OutputFormat can make sure the schema will translate in a well defined way. Default implementation is a no-op.

Specified by:

checkSchema in interface StoreFuncInterface

Overrides:

checkSchema in class StoreFunc

Parameters:

s - to be checked

Throws:

java.io.IOException - if this schema is not acceptable. It should include a detailed error message indicating what is wrong with the schema.

prepareToWrite

public void prepareToWrite(org.apache.hadoop.mapreduce.RecordWriter writer)
                    throws java.io.IOException

Description copied from class: StoreFunc

Initialize StoreFunc to write data. This will be called during execution on the backend before the call to putNext.

Specified by:

prepareToWrite in interface StoreFuncInterface

Specified by:

prepareToWrite in class StoreFunc

Parameters:

writer - RecordWriter to use.

Throws:

java.io.IOException - if an exception occurs during initialization

putNext

public void putNext(Tuple t)
             throws java.io.IOException

Description copied from class: StoreFunc

Write a tuple to the data store.

Specified by:

putNext in interface StoreFuncInterface

Specified by:

putNext in class StoreFunc

Parameters:

t - the tuple to store.

Throws:

java.io.IOException - if an exception occurs during the write

storeStatistics

public void storeStatistics(ResourceStatistics stats,
                            java.lang.String location,
                            org.apache.hadoop.mapreduce.Job job)
                     throws java.io.IOException

Description copied from interface: StoreMetadata

Store statistics about the data being written.

Specified by:

storeStatistics in interface StoreMetadata

Parameters:

stats - statistics to be recorded

location - Location as returned by LoadFunc.relativeToAbsolutePath(String, org.apache.hadoop.fs.Path)

job - The Job object - this should be used only to obtain cluster properties through JobContextImpl.getConfiguration() and not to set/query any runtime job information.

Throws:

java.io.IOException

storeSchema

public void storeSchema(ResourceSchema schema,
                        java.lang.String location,
                        org.apache.hadoop.mapreduce.Job job)
                 throws java.io.IOException

Description copied from interface: StoreMetadata

Store schema of the data being written

Specified by:

storeSchema in interface StoreMetadata

Parameters:

schema - Schema to be recorded

location - Location as returned by LoadFunc.relativeToAbsolutePath(String, org.apache.hadoop.fs.Path)

job - The Job object - this should be used only to obtain cluster properties through JobContextImpl.getConfiguration() and not to set/query any runtime job information.

Throws:

java.io.IOException

fixSchema

public ResourceSchema fixSchema(ResourceSchema s)

getShipFiles

public java.util.List<java.lang.String> getShipFiles()

Description copied from interface: StoreResources

Allow a StoreFunc to specify a list of files located locally and would like to ship to backend (through distributed cache). Check for FuncUtils for utility function to facilitate it The default implementation returns null.

Specified by:

getShipFiles in interface StoreResources

Returns:

A list of files

getCacheFiles

public java.util.List<java.lang.String> getCacheFiles()

Description copied from interface: StoreResources

Allow a StoreFunc to specify a list of files it would like placed in the distributed cache. The default implementation returns null.

Specified by:

getCacheFiles in interface StoreResources

Returns:

A list of files

supportsParallelWriteToStoreLocation

public java.lang.Boolean supportsParallelWriteToStoreLocation()

Description copied from interface: StoreFuncInterface

DAG execution engines like Tez support optimizing union by writing to output location in parallel from tasks of different vertices. Commit is called once all the vertices in the union are complete. This eliminates need to have a separate phase to read data output from previous phases, union them and write out again. Enabling the union optimization requires the OutputFormat to 1) Support creation of different part file names for tasks of different vertices. Conflicting filenames can create data corruption and loss. For eg: If task 0 of vertex1 and vertex2 both create filename as part-r-00000, then one of the files will be overwritten when promoting from temporary to final location leading to data loss. FileOutputFormat has mapreduce.output.basename config which enables naming files differently in different vertices. Classes extending FileOutputFormat and those prefixing file names with mapreduce.output.basename value will not encounter conflict. Cases like HBaseStorage which write to key value store and do not produce files also should not face any conflict. 2) Support calling of commit once at the end takes care of promoting temporary files of the different vertices into the final location. For eg: FileOutputFormat commit algorithm handles promoting of files produced by tasks of different vertices into final output location without issues if there is no file name conflict. In cases like HBaseStorage, the TableOutputCommitter does nothing on commit. If custom OutputFormat used by the StoreFunc does not support the above two criteria, then false should be returned. Union optimization will be disabled for the StoreFunc. Default implementation returns null and in that case planner falls back to PigConfiguration.PIG_TEZ_OPT_UNION_SUPPORTED_STOREFUNCS and PigConfiguration.PIG_TEZ_OPT_UNION_UNSUPPORTED_STOREFUNCS settings to determine if the StoreFunc supports it.

Specified by:

supportsParallelWriteToStoreLocation in interface StoreFuncInterface