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##
## Required Properties
##

#dataInputFormat -- required -- 'base', 'elasticsearch', or 'standalone' -- Specify the input format
pir.dataInputFormat=

#outputFile -- required -- Fully qualified name of output file in hdfs
pir.outputFile=

#platform -- required -- 'mapreduce', 'spark', or 'standalone'
#Processing platform technology for the responder                
platform= 

#queryInput -- required -- Fully qualified dir in hdfs of Query files
pir.queryInput=


##
## Optional Args - Leave empty if not using/not changing default values
##

#inputData -- required if baseInputFormat = 'base'
#Fully qualified name of input file/directory in hdfs; used if inputFormat = 'base'
#pir.inputData=
 
#dataSchemas -- optional -- Comma separated list of data schema file names to load
#responder.dataSchemas=

#querySchemas -- optional -- Comma separated list of query schema file names to load
#responder.querySchemas=                                    

#allowAdHocQuerySchemas -- 'true' or 'false'
#If true, allows embedded QuerySchemas for a query.
#Defaults to 'false'
#pir.allowEmbeddedQuerySchemas=

#colMultReduceByKey -- 'true' or 'false' -- Spark only
#If true, uses reduceByKey in performing column multiplication; if false, uses groupByKey -> reduce
#Defaults to 'false' 
#pir.colMultReduceByKey=

#baseInputFormat -- required if baseInputFormat = 'base'
#Full class name of the InputFormat to use when reading in the data - must extend BaseInputFormat
#pir.baseInputFormat=

#esQuery -- required if baseInputFormat = 'elasticsearch' -- ElasticSearch query
#if using 'elasticsearch' input format
#pir.esQuery=

#esResource --  required if baseInputFormat = 'elasticsearch'
#Requires the format <index>/<type> : Elasticsearch resource where data is read and written to
#pir.esResource=

#useHDFSLookupTable -- 'true' or 'false' - Whether or not to generate and use the
#hdfs lookup table for modular exponentiation
#Defaults to 'false'
#pir.useHDFSLookupTable=

#baseQuery -- ElasticSearch-like query if using 'base' input format -
#used to filter records in the RecordReader
#Defaults to ?q=*
#pir.baseQuery=

#limitHitsPerSelector -- 'true' or 'false'
#Whether or not to limit the number of hits per selector
#Defaults to 'true'
#pir.limitHitsPerSelector=

#mapreduceMapJavaOpts -- Amount of heap (in MB) to allocate per map task
#Defaults to -Xmx2800m
#mapreduce.map.java.opts=

#mapreduceMapMemoryMb -- Amount of memory (in MB) to allocate per map task
#Defaults to 3000
#mapreduce.map.memory.mb=
     
#mapreduceReduceJavaOpts
#Amount of heap (in MB) to allocate per reduce task
#Defaults to -Xmx2800m
#mapreduce.reduce.java.opts=

#mapreduceReduceMemoryMb
#Amount of memory (in MB) to allocate per reduce task
#Defaults to 3000
#mapreduce.reduce.memory.mb=

#stopListFile -- optional (unless using StopListFilter) -- Fully qualified file in hdfs
#containing stoplist terms; used by the StopListFilter
#pir.stopListFile=

#useLocalCache -- 'true' or 'false'
#Whether or not to use the local cache for modular exponentiation
#Defaults to 'true'
#pir.useLocalCache=

#useModExpJoin -- 'true' or 'false' -- Spark only
#Whether or not to pre-compute the modular exponentiation table and join it to the data
#partitions when performing the encrypted row calculations
#Defaults to 'false'
#pir.useModExpJoin=

#numReduceTasks -- optional -- Number of reduce tasks
#pir.numReduceTasks=

#numColMultPartitions -- optional, Spark only
#Number of partitions to use when performing  column multiplication
#pir.numColMultPartitions=        

#maxHitsPerSelector --  optional -- Max number of hits encrypted per selector
#pir.maxHitsPerSelector=

#dataParts -- optional -- Number of partitions for the input data
#pir.numDataPartitions=

#numExpLookupPartitions -- optional -- Number of partitions for the exp lookup table
#pir.numExpLookupPartitions=