conf/pig.properties

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# specific language governing permissions and limitations
# under the License.

# Pig configuration file. All values can be overwritten by command line arguments.

# Use the "-h properties" command to see description of the properties

# log4jconf log4j configuration file
# log4jconf=./conf/log4j.properties

# a file that contains pig script
#file=

# load jarfile, colon separated
#jar=

#verbose print all log messages to screen (default to print only INFO and above to screen)
#verbose=true

#exectype local|mapreduce, mapreduce is default
#exectype=local

#the default timezone: if it is not set, the default timezone for this host is used.
#the correct timezone format is the UTC offset: e.g., +08:00. 
#pig.datetime.default.tz=

#pig.logfile=

#Do not spill temp files smaller than this size (bytes)
#pig.spill.size.threshold=5000000

#EXPERIMENT: Activate garbage collection when spilling a file bigger than this size (bytes)
#This should help reduce the number of files being spilled.
#pig.spill.gc.activation.size=40000000

#the following two parameters are to help estimate the reducer number
#pig.exec.reducers.bytes.per.reducer=1000000000
#pig.exec.reducers.max=999

#Logging properties
#verbose=false
#brief=false
#debug=INFO
#aggregate.warning=true

#Performance tuning properties
#pig.cachedbag.memusage=0.2
#pig.skewedjoin.reduce.memusagea=0.3
#pig.exec.nocombiner=false
#opt.multiquery=true
#pig.tmpfilecompression=false

#value can be lzo or gzip
#pig.tmpfilecompression.codec=gzip
#pig.noSplitCombination=true

#pig.exec.mapPartAgg=false
#pig.exec.mapPartAgg.minReduction=10

#exectype=mapreduce
#pig.additional.jars=<comma seperated list of jars>
#udf.import.list=<comma seperated list of imports>
#stop.on.failure=false

#Use this option only when your Pig job will otherwise die because of
#using more counters than hadoop configured limit
#pig.disable.counter=true

# Use this option to turn on UDF timers. This will cause two 
# counters to be tracked for every UDF and LoadFunc in your script:
# approx_microsecs measures approximate time spent inside a UDF
# approx_invocations reports the approximate number of times the UDF was invoked
# pig.udf.profile=false

#When enabled, 'describe' prints a multi-line formatted schema
#(similar to an indended json) rather than on a single line.
#pig.pretty.print.schema=true

#pig.sql.type=hcat
hcat.bin=/usr/local/hcat/bin/hcat

############################ SchemaTuple ############################

# Setting this value will turn on the SchemaTuple feature (PIG-2632)
# This will attempt to use code generation for more efficient within
# the pig code. This can lead to both CPU, serialization, and memory
# benefits (currently, the potential memory benefits are the largest).

# This parameter will enable the optimization in all available cases
#pig.schematuple=true

# Certain cases can be turned off by uncommenting the following. These will
# all be off by default, but will all be turned on if pig.schematuple is set
# to true.

# This will disable SchemaTuples in the case of udfs. Currently,
# the input to UDF's will be SchemaTuples.

#pig.schematuple.udf=false

# This is currently not implemented. In the future, LoadFunc's with known
# schema's should output SchemaTuples

#pig.schematuple.load=false

# This will use SchemaTuples in replicated joins. The potential memory saving
# here is significant. It will use SchemaTuples when it builds the HashMap of
# the join key to related values.

#pig.schematuple.fr_join=false

# In the current implementation of merge join, all of the Tuples in the left relation
# that share a given key will be stored in a List in memory. This will use SchemaTuples
# instead in that List.

#pig.schematuple.merge_join=false

#####################################################################

##### Set up optional Pig Progress Notification Listener ############

# Note that only one PPNL can be set up. If you need several, write a PPNL that will chain them.
# pig.notification.listener = <fully qualified class name of a PPNL implementation>

# Optionally, you can supply a single String argument to pass to your PPNL. 
# pig.notification.listener.arg = <somevalue>

#####################################################################

########## Override the default Reducer Estimator logic #############

# By default, the logic to estimate the number of reducers to use for a given job lives in:
#   org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.InputSizeReducerEstimator
# This logic can be relaced by implementing the following interface:
#   org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigReducerEstimator

# This class will be invoked to estimate the number of reducers to use.
# pig.exec.reducer.estimator = <fully qualified class name of a PigReducerEstimator implementation>

# Optionally, you can supply a single String argument to pass to your PigReducerEstimator.
# pig.exec.reducer.estimator.arg = <somevalue>

#####################################################################

#pig.load.default.statements=