Apache PIG, ELEPHANTBIRDJSON Loader - hadoop
I'm trying to parse below input (there are 2 records in this input)using Elephantbird json loader
[{"node_disk_lnum_1":36,"node_disk_xfers_in_rate_sum":136.40000000000001,"node_disk_bytes_in_rate_22":
187392.0, "node_disk_lnum_7": 13}]
[{"node_disk_lnum_1": 36, "node_disk_xfers_in_rate_sum":
105.2,"node_disk_bytes_in_rate_22": 123084.8, "node_disk_lnum_7":13}]
Here is my syntax:
register '/home/data/Desktop/elephant-bird-pig-4.1.jar';
a = LOAD '/pig/tc1.log' USING
com.twitter.elephantbird.pig.load.JsonLoader('-nestedLoad') as (json:map[]);
b = FOREACH a GENERATE flatten(json#'node_disk_lnum_1') AS
node_disk_lnum_1,flatten(json#'node_disk_xfers_in_rate_sum') AS
node_disk_xfers_in_rate_sum,flatten(json#'node_disk_bytes_in_rate_22') AS
node_disk_bytes_in_rate_22, flatten(json#'node_disk_lnum_7') AS
node_disk_lnum_7;
DESCRIBE b;
b describe result:
b: {node_disk_lnum_1: bytearray,node_disk_xfers_in_rate_sum:
bytearray,node_disk_bytes_in_rate_22: bytearray,node_disk_lnum_7:
bytearray}
c = FOREACH b GENERATE node_disk_lnum_1;
DESCRIBE c;
c: {node_disk_lnum_1: bytearray}
DUMP c;
Expected Result:
36, 136.40000000000001, 187392.0, 13
36, 105.2, 123084.8, 13
Throwing the below error
2017-02-06 01:05:49,337 [main] INFO
org.apache.pig.tools.pigstats.ScriptState - Pig features used in the
script: UNKNOWN 2017-02-06 01:05:49,386 [main] INFO
org.apache.pig.data.SchemaTupleBackend - Key [pig.schematuple] was not
set... will not generate code. 2017-02-06 01:05:49,387 [main] INFO
org.apache.pig.newplan.logical.optimizer.LogicalPlanOptimizer -
{RULES_ENABLED=[AddForEach, ColumnMapKeyPrune, ConstantCalculator,
GroupByConstParallelSetter, LimitOptimizer, LoadTypeCastInserter,
MergeFilter, MergeForEach, PartitionFilterOptimizer,
PredicatePushdownOptimizer, PushDownForEachFlatten, PushUpFilter,
SplitFilter, StreamTypeCastInserter]} 2017-02-06 01:05:49,390 [main]
INFO org.apache.pig.newplan.logical.rules.ColumnPruneVisitor - Map
key required for a: $0->[node_disk_lnum_1,
node_disk_xfers_in_rate_sum, node_disk_bytes_in_rate_22,
node_disk_lnum_7]
2017-02-06 01:05:49,395 [main] INFO
org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler
- File concatenation threshold: 100 optimistic? false 2017-02-06 01:05:49,398 [main] INFO
org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer
- MR plan size before optimization: 1 2017-02-06 01:05:49,398 [main] INFO
org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer
- MR plan size after optimization: 1 2017-02-06 01:05:49,425 [main] INFO org.apache.pig.tools.pigstats.mapreduce.MRScriptState - Pig
script settings are added to the job 2017-02-06 01:05:49,426 [main]
INFO
org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler
- mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3 2017-02-06 01:05:49,428 [main] ERROR
org.apache.pig.tools.grunt.Grunt - ERROR 2998: Unhandled internal
error. com/twitter/elephantbird/util/HadoopCompat
Please help what am I missing?
You do not have any nested data in your json,so remove -nestedload
a = LOAD '/pig/tc1.log' USING com.twitter.elephantbird.pig.load.JsonLoader() as (json:map[]);
Related
PIG : count of each product in distinctive Locations
I am trying to do following Step1 to Step4 in pig: STEP 1:- Create a user table:and take data from /tmp/users.txt- |Column 1 | USER ID |int| |Column 2 |EMAIL|chararray| |Column 3 |LANGUAGE |chararray| |Column 4 |LOCATION |chararray| STEP 2:- Crate a transaction table and take data from /tmp/transaction.txt:- |Column 1 | ID |int| |Column 2 |PRODUCT|int| |Column 3 |USER ID |int| |Column 4 |PURCHASE AMOUNT |double| |Coulmn 5 |DESCRIPTION |chararray| Step 3:- Find out the count of each product in distinctive Locations. Step 4:- Display the results. For achieving above I did the following : users = LOAD '/tmp/users.txt' USING PigStorage(',') AS (USERID:int, EMAIL:chararray, LANGUAGE:chararray, LOCATION: chararray); trans = LOAD '/tmp/transaction.txt' USING PigStorage(',') AS (ID:int, PRODUCT:int, USERID:int, PURCHASEAMOUNT: double, DESCRIPTION: chararray); users_trans = JOIN users BY USERID RIGHT, trans BY USERID; B = GROUP users_trans BY (DESCRIPTION,LOCATION); C = FOREACH B GENERATE group as comb, COUNT(users_trans) AS Total; DUMP C; But, I am getting errors.. It will helpful if you assist as I am new to pig. ########################################## Dataset user.txt 1 creator#gmail.com EN US 2 creator#gmail.com EN GB 3 creator#gmail.com FR FR 4 creator#gmail.com IN HN 5 creator#gmail.com PAK IS transaction.txt 1 1 1 300 a jumper 2 1 2 300 a jumper 3 1 5 300 a jumper 4 2 3 100 a rubber chicken 5 1 3 300 a jumper 6 5 4 500 a soapbox 7 3 3 200 a adhesive 8 4 1 300 a lotion 9 4 4 500 a sweater 10 5 4 600 a jeans Error Log: 2019-12-27 06:17:22,180 [LocalJobRunner Map Task Executor #0] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigRecordReader - Current split being processed file:/tmp/temp2029752934/tmp-883821114/part-r-00000:0+130 2019-12-27 06:17:22,242 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - (EQUATOR) 0 kvi 26214396(104857584) 2019-12-27 06:17:22,242 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - mapreduce.task.io.sort.mb: 100 2019-12-27 06:17:22,242 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - soft limit at 83886080 2019-12-27 06:17:22,242 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - bufstart = 0; bufvoid = 104857600 2019-12-27 06:17:22,242 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - kvstart = 26214396; length = 6553600 2019-12-27 06:17:22,244 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer 2019-12-27 06:17:22,248 [LocalJobRunner Map Task Executor #0] INFO org.apache.pig.impl.util.SpillableMemoryManager - Selected heap (PS Old Gen) of size 699400192 to monitor. collectionUsageThreshold = 489580128, usageThreshold = 489580128 2019-12-27 06:17:22,248 [LocalJobRunner Map Task Executor #0] WARN org.apache.pig.data.SchemaTupleBackend - SchemaTupleBackend has already been initialized 2019-12-27 06:17:22,250 [LocalJobRunner Map Task Executor #0] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapReduce$Map - Aliases being processed per job phase (AliasName[line,offset]): M: C[7,4],B[6,4] C: C[7,4],B[6,4] R: C[7,4] 2019-12-27 06:17:22,254 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.LocalJobRunner - 2019-12-27 06:17:22,254 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - Starting flush of map output 2019-12-27 06:17:22,254 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - Spilling map output 2019-12-27 06:17:22,254 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - bufstart = 0; bufend = 100; bufvoid = 104857600 2019-12-27 06:17:22,254 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - kvstart = 26214396(104857584); kvend = 26214360(104857440); length = 37/6553600 2019-12-27 06:17:22,262 [LocalJobRunner Map Task Executor #0] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigCombiner$Combine - Aliases being processed per job phase (AliasName[line,offset]): M: C[7,4],B[6,4] C: C[7,4],B[6,4] R: C[7,4] 2019-12-27 06:17:22,264 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.MapTask - Finished spill 0 2019-12-27 06:17:22,265 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.Task - Task:attempt_local1424814286_0002_m_000000_0 is done. And is in the process of committing 2019-12-27 06:17:22,266 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.LocalJobRunner -map 2019-12-27 06:17:22,266 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.Task - Task 'attempt_local1424814286_0002_m_000000_0' done. 2019-12-27 06:17:22,266 [LocalJobRunner Map Task Executor #0] INFO org.apache.hadoop.mapred.LocalJobRunner -Finishing task: attempt_local1424814286_0002_m_000000_0 2019-12-27 06:17:22,266 [Thread-18] INFO org.apache.hadoop.mapred.LocalJobRunner - map task executor complete. 2019-12-27 06:17:22,266 [Thread-18] INFO org.apache.hadoop.mapred.LocalJobRunner - Waiting for reduce tasks 2019-12-27 06:17:22,267 [pool-9-thread-1] INFO org.apache.hadoop.mapred.LocalJobRunner - Starting task: attempt_local1424814286_0002_r_000000_0 2019-12-27 06:17:22,272 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - File Output Committer Algorithm version is 1 2019-12-27 06:17:22,272 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - FileOutputCommitter skip cleanup _temporary folders under output directory:false, ignore cleanup failures: false 2019-12-27 06:17:22,274 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Task - Using ResourceCalculatorProcessTree : [ ] 2019-12-27 06:17:22,274 [pool-9-thread-1] INFO org.apache.hadoop.mapred.ReduceTask - Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle#2582aa54 2019-12-27 06:17:22,275 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl - MergerManager: memoryLimit=652528832, maxSingleShuffleLimit=163132208, mergeThreshold=430669056, ioSortFactor=10, memToMemMergeOutputsThreshold=10 2019-12-27 06:17:22,275 [EventFetcher for fetching Map Completion Events] INFO org.apache.hadoop.mapreduce.task.reduce.EventFetcher - attempt_local1424814286_0002_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events 2019-12-27 06:17:22,276 [localfetcher#2] INFO org.apache.hadoop.mapreduce.task.reduce.LocalFetcher - localfetcher#2 about to shuffle output of map attempt_local1424814286_0002_m_000000_0 decomp: 14 len: 18 to MEMORY 2019-12-27 06:17:22,277 [localfetcher#2] INFO org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput - Read 14 bytes from map-output for attempt_local1424814286_0002_m_000000_0 2019-12-27 06:17:22,277 [localfetcher#2] INFO org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl - closeInMemoryFile -> map-output of size: 14, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->14 2019-12-27 06:17:22,277 [EventFetcher for fetching Map Completion Events] INFO org.apache.hadoop.mapreduce.task.reduce.EventFetcher - EventFetcher is interrupted.. Returning 2019-12-27 06:17:22,278 [Readahead Thread #3] WARN org.apache.hadoop.io.ReadaheadPool - Failed readahead on ifile EBADF: Bad file descriptor at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posix_fadvise(Native Method) at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posixFadviseIfPossible(NativeIO.java:267) at org.apache.hadoop.io.nativeio.NativeIO$POSIX$CacheManipulator.posixFadviseIfPossible(NativeIO.java:146) at org.apache.hadoop.io.ReadaheadPool$ReadaheadRequestImpl.run(ReadaheadPool.java:208) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) 2019-12-27 06:17:22,278 [pool-9-thread-1] INFO org.apache.hadoop.mapred.LocalJobRunner - 1 / 1 copied. 2019-12-27 06:17:22,280 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl - finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs 2019-12-27 06:17:22,280 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Merger - Merging 1 sorted segments 2019-12-27 06:17:22,280 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Merger - Down to the last merge-pass, with 1 segments left of total size: 7 bytes 2019-12-27 06:17:22,281 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl - Merged 1 segments, 14 bytes to disk to satisfy reduce memory limit 2019-12-27 06:17:22,281 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl - Merging 1 files, 18 bytes from disk 2019-12-27 06:17:22,281 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl - Merging 0 segments, 0 bytes from memory into reduce 2019-12-27 06:17:22,281 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Merger - Merging 1 sorted segments 2019-12-27 06:17:22,281 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Merger - Down to the last merge-pass, with 1 segments left of total size: 7 bytes 2019-12-27 06:17:22,282 [pool-9-thread-1] INFO org.apache.hadoop.mapred.LocalJobRunner - 1 / 1 copied. 2019-12-27 06:17:22,283 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - File Output Committer Algorithm version is 1 2019-12-27 06:17:22,283 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - FileOutputCommitter skip cleanup _temporary folders under output directory:false, ignore cleanup failures: false 2019-12-27 06:17:22,284 [pool-9-thread-1] INFO org.apache.pig.impl.util.SpillableMemoryManager - Selected heap (PS Old Gen) of size 699400192 to monitor. collectionUsageThreshold = 489580128, usageThreshold = 489580128 2019-12-27 06:17:22,285 [pool-9-thread-1] WARN org.apache.pig.data.SchemaTupleBackend - SchemaTupleBackend has already been initialized 2019-12-27 06:17:22,286 [pool-9-thread-1] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigMapReduce$Reduce - Aliases being processed per job phase (AliasName[line,offset]): M: C[7,4],B[6,4] C: C[7,4],B[6,4] R: C[7,4] 2019-12-27 06:17:22,287 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Task - Task:attempt_local1424814286_0002_r_000000_0 is done. And is in the process of committing 2019-12-27 06:17:22,289 [pool-9-thread-1] INFO org.apache.hadoop.mapred.LocalJobRunner - 1 / 1 copied. 2019-12-27 06:17:22,289 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Task - Task attempt_local1424814286_0002_r_000000_0 is allowed to commit now 2019-12-27 06:17:22,292 [pool-9-thread-1] INFO org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - Saved output of task 'attempt_local1424814286_0002_r_000000_0' to file:/tmp/temp2029752934/tmp726323435/_temporary/0/task_local1424814286_0002_r_000000 2019-12-27 06:17:22,292 [pool-9-thread-1] INFO org.apache.hadoop.mapred.LocalJobRunner - reduce > reduce 2019-12-27 06:17:22,292 [pool-9-thread-1] INFO org.apache.hadoop.mapred.Task - Task 'attempt_local1424814286_0002_r_000000_0' done. 2019-12-27 06:17:22,292 [pool-9-thread-1] INFO org.apache.hadoop.mapred.LocalJobRunner - Finishing task: attempt_local1424814286_0002_r_000000_0 2019-12-27 06:17:22,292 [Thread-18] INFO org.apache.hadoop.mapred.LocalJobRunner - reduce task executor complete. 2019-12-27 06:17:22,460 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - HadoopJobId: job_local1424814286_0002 2019-12-27 06:17:22,460 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Processing aliases B,C 2019-12-27 06:17:22,460 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - detailed locations: M: C[7,4],B[6,4] C: C[7,4],B[6,4] R: C[7,4] 2019-12-27 06:17:22,463 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,464 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,465 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,471 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 100% complete 2019-12-27 06:17:22,474 [main] INFO org.apache.pig.tools.pigstats.mapreduce.SimplePigStats - Script Statistics: HadoopVersion PigVersion UserId StartedAt FinishedAt Features 2.9.2 0.16.0 root 2019-12-27 06:17:20 2019-12-27 06:17:22 HASH_JOIN,GROUP_BY Success! Job Stats (time in seconds): JobId Maps Reduces MaxMapTime MinMapTime AvgMapTime MedianMapTime MaxReduceTime MinReduceTime AvgReduceTime MedianReducetime Alias Feature Outputs job_local1289071959_0001 2 1 n/a n/a n/a n/a n/a n/a n/a n/a trans,users,users_trans HASH_JOIN job_local1424814286_0002 1 1 n/a n/a n/a n/a n/a n/a n/a n/a B,C GROUP_BY,COMBINER file:/tmp/temp2029752934/tmp726323435, Input(s): Successfully read 5 records from: "/tmp/users.txt" Successfully read 10 records from: "/tmp/transaction.txt" Output(s): Successfully stored 1 records in: "file:/tmp/temp2029752934/tmp726323435" Counters: Total records written : 1 Total bytes written : 0 Spillable Memory Manager spill count : 0 Total bags proactively spilled: 0 Total records proactively spilled: 0 Job DAG: job_local1289071959_0001 -> job_local1424814286_0002, job_local1424814286_0002 2019-12-27 06:17:22,475 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,476 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,477 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,485 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,486 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,487 [main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Cannot initialize JVM Metricswith processName=JobTracker, sessionId= - already initialized 2019-12-27 06:17:22,492 [main] WARN org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Encountered Warning FIELD_DISCARDED_TYPE_CONVERSION_FAILED 15 time(s). 2019-12-27 06:17:22,493 [main] WARN org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Encountered Warning ACCESSING_NON_EXISTENT_FIELD 55 time(s). 2019-12-27 06:17:22,493 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success! 2019-12-27 06:17:22,496 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2019-12-27 06:17:22,496 [main] WARN org.apache.pig.data.SchemaTupleBackend - SchemaTupleBackend has already been initialized 2019-12-27 06:17:22,503 [main] INFO org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input files to process : 1 2019-12-27 06:17:22,503 [main] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1 2019-12-27 06:17:22,541 [main] INFO org.apache.pig.Main - Pig script completed in 2 seconds and 965 milliseconds (2965 ms)
Advice First of all: It seems that you are starting up with Pig. It may be valuable to know that Cloudera recently decided to deprecate Pig. It will of course not cease to exist, but think twice if you are planning to pick up a new skill or implement new use cases. I would recommend looking into Hive/Spark/Impala as more future proof alternatives. Answer Your job succeeds, but presumably not with output you want. There are several hints to what may be wrong (data types/field names) however this does not point at a specific problem in the code. My recommendation would be to find out where the problem exactly occurs. Simply cut off the end of your code and print an intermediate result to see if you are still on track. In the (likely) event you have a problem in your load statement already, it is worth noting that you can still narrow it down further. First load, and then apply the schema.
Given the data you have, first problem would be that you have no commas, so you must load the lines as a whole, then split them later. I used two or more spaces in the transactions file because your last column appears to be one string containing spaces. For accuracy, I suggest having a better delimiter than spaces/tabs. Then the group by needs to reference the relations that the data comes from. Everything else is fine, I think, though I'm not sure about the COUNT(X) A = LOAD '/tmp/users.txt' USING PigStorage() as (line:chararray); USERS = FOREACH A GENERATE FLATTEN(STRSPLIT(line, '\\s+')) AS (userid:int,email:chararray,language:chararray,location:chararray); B = LOAD '/tmp/transactions.txt' USING PigStorage() as (line:chararray); TRANS = FOREACH B GENERATE FLATTEN(STRSPLIT(line, '\\s\\s+')) AS (id:int,product:int,userid:int,purchase:double,desc:chararray); X = JOIN USERS BY userid RIGHT, TRANS BY userid; X_grouped = GROUP X BY (TRANS::desc, USERS::location); RES = FOREACH X_grouped GENERATE group as comb, COUNT(X) AS Total; \d RES; Output ((a jeans,HN),1) ((a jumper,FR),1) ((a jumper,GB),1) ((a jumper,IS),1) ((a jumper,US),1) ((a lotion,US),1) ((a soapbox,HN),1) ((a sweater,HN),1) ((a adhesive,FR),1) ((a rubber chicken,FR),1)
Does sqoop spill temporary data to disk
As I understand sqoop, it launches few mappers on different data nodes making jdbc connection with RDBMS. Once connection is formed data is transferred to HDFS. Just trying to understand, does sqoop mapper spill data temporary on disk (data node)? I know spilling happens in MapReduce but not sure about sqoop job.
It seems sqoop-import runs on mapper and doesn't spill. And sqoop-merge runs on map-reduce and does spill. You can check it on Job tracker during sqoop import run. Have a look at this part of sqoop import log, it does not spill, fetches and writes to hdfs: INFO [main] ... mapreduce.db.DataDrivenDBRecordReader: Using query: SELECT... [main] mapreduce.db.DBRecordReader: Executing query: SELECT... INFO [main] org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter: File Output Committer Algorithm version is 1 INFO [main] org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter: FileOutputCommitter skip cleanup _temporary folders under output directory:false, ignore cleanup failures: false INFO [main] org.apache.hadoop.io.compress.CodecPool: Got brand-new compressor [.snappy] INFO [Thread-16] ...mapreduce.AutoProgressMapper: Auto-progress thread is finished. keepGoing=false INFO [main] org.apache.hadoop.mapred.Task: Task:attempt_1489705733959_2462784_m_000000_0 is done. And is in the process of committing INFO [main] org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter: Saved output of task 'attempt_1489705733959_2462784_m_000000_0' to hdfs:// Have a look at this sqoop-merge log(skipped some rows), it spills on disk (note Spilling map output in the log): INFO [main] org.apache.hadoop.mapred.MapTask: Processing split: hdfs://bla-bla/part-m-00000:0+48322717 ... INFO [main] org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter: FileOutputCommitter skip cleanup _temporary folders under output directory:false, ignore cleanup failures: false ... INFO [main] org.apache.hadoop.mapred.MapTask: mapreduce.task.io.sort.mb: 1024 INFO [main] org.apache.hadoop.mapred.MapTask: soft limit at 751619264 INFO [main] org.apache.hadoop.mapred.MapTask: bufstart = 0; bufvoid = 1073741824 INFO [main] org.apache.hadoop.mapred.MapTask: kvstart = 268435452; length = 67108864 INFO [main] org.apache.hadoop.mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$**MapOutputBuffer** INFO [main] com.pepperdata.supervisor.agent.resource.r: Datanode bla-bla is LOCAL. INFO [main] org.apache.hadoop.io.compress.CodecPool: Got brand-new decompressor [.snappy] ... INFO [main] org.apache.hadoop.mapred.MapTask: **Starting flush of map output** INFO [main] org.apache.hadoop.mapred.MapTask: **Spilling map output** INFO [main] org.apache.hadoop.mapred.MapTask: **bufstart** = 0; **bufend** = 184775274; bufvoid = 1073741824 INFO [main] org.apache.hadoop.mapred.MapTask: kvstart = 268435452(1073741808); kvend = 267347800(1069391200); length = 1087653/67108864 INFO [main] org.apache.hadoop.io.compress.CodecPool: Got brand-new compressor [.snappy] [main] org.apache.hadoop.mapred.MapTask: Finished spill 0 ...Task:attempt_1489705733959_2479291_m_000000_0 is done. And is in the process of committing
How to divert the output of pig command to a text file in order to print it out?
2015-09-24 01:59:28,436 [main] INFO org.apache.pig.newplan.logical.optimizer.LogicalPlanOptimizer - {RULES_ENABLED=[AddForEach, ColumnMapKeyPrune, ConstantCalculator, GroupByConstParallelSetter, LimitOptimizer, LoadTypeCastInserter, MergeFilter, MergeForEach, PartitionFilterOptimizer, PredicatePushdownOptimizer, PushDownForEachFlatten, PushUpFilter, SplitFilter, StreamTypeCastInserter]} 2015-09-24 01:59:28,539 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2015-09-24 01:59:28,556 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler - File concatenation threshold: 100 optimistic? false 2015-09-24 01:59:28,560 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - MR plan size before optimization: 1 2015-09-24 01:59:28,561 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - MR plan size after optimization: 1 2015-09-24 01:59:28,620 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2015-09-24 01:59:28,624 [main] INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at /0.0.0.0:8032 2015-09-24 01:59:28,638 [main] INFO org.apache.pig.tools.pigstats.mapreduce.MRScriptState - Pig script settings are added to the job 2015-09-24 01:59:28,640 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3 2015-09-24 01:59:28,641 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - This job cannot be converted run in-process 2015-09-24 01:59:29,268 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Added jar file:/home/vivek/Applications/pig/pig-0.14.0-core-h2.jar to DistributedCache through /tmp/temp-1176581946/tmp-2078805221/pig-0.14.0-core-h2.jar 2015-09-24 01:59:29,452 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Added jar file:/home/vivek/Applications/pig/lib/automaton-1.11-8.jar to DistributedCache through /tmp/temp-1176581946/tmp-1750967439/automaton-1.11-8.jar 2015-09-24 01:59:29,538 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Added jar file:/home/vivek/Applications/pig/lib/antlr-runtime-3.4.jar to DistributedCache through /tmp/temp-1176581946/tmp1997290065/antlr-runtime-3.4.jar 2015-09-24 01:59:29,843 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Added jar file:/home/vivek/Applications/hadoop/share/hadoop/common/lib/guava-11.0.2.jar to DistributedCache through /tmp/temp-1176581946/tmp-256046780/guava-11.0.2.jar 2015-09-24 01:59:29,990 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Added jar file:/home/vivek/Applications/pig/lib/joda-time-2.1.jar to DistributedCache through /tmp/temp-1176581946/tmp955728106/joda-time-2.1.jar 2015-09-24 01:59:30,129 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Setting up single store job 2015-09-24 01:59:30,131 [main] INFO org.apache.pig.data.SchemaTupleFrontend - Key [pig.schematuple] is false, will not generate code. 2015-09-24 01:59:30,131 [main] INFO org.apache.pig.data.SchemaTupleFrontend - Starting process to move generated code to distributed cacche 2015-09-24 01:59:30,132 [main] INFO org.apache.pig.data.SchemaTupleFrontend - Setting key [pig.schematuple.classes] with classes to deserialize [] 2015-09-24 01:59:30,276 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 1 map-reduce job(s) waiting for submission. 2015-09-24 01:59:30,283 [JobControl] INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at /0.0.0.0:8032 2015-09-24 01:59:30,568 [JobControl] WARN org.apache.hadoop.mapreduce.JobSubmitter - No job jar file set. User classes may not be found. See Job or Job#setJar(String). 2015-09-24 01:59:30,868 [JobControl] INFO org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 1 2015-09-24 01:59:30,871 [JobControl] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1 2015-09-24 01:59:30,874 [JobControl] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths (combined) to process : 1 2015-09-24 01:59:31,190 [JobControl] INFO org.apache.hadoop.mapreduce.JobSubmitter - number of splits:1 2015-09-24 01:59:31,499 [JobControl] INFO org.apache.hadoop.mapreduce.JobSubmitter - Submitting tokens for job: job_1443082231600_0003 2015-09-24 01:59:31,516 [JobControl] INFO org.apache.hadoop.mapred.YARNRunner - Job jar is not present. Not adding any jar to the list of resources. 2015-09-24 01:59:31,704 [JobControl] INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1443082231600_0003 2015-09-24 01:59:31,738 [JobControl] INFO org.apache.hadoop.mapreduce.Job - The url to track the job: http://ubuntu:8088/proxy/application_1443082231600_0003/ 2015-09-24 01:59:31,742 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - HadoopJobId: job_1443082231600_0003 2015-09-24 01:59:31,745 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Processing aliases highsal,salaries 2015-09-24 01:59:31,745 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - detailed locations: M: salaries[3,10],salaries[-1,-1],highsal[13,9] C: R: 2015-09-24 01:59:31,781 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 0% complete 2015-09-24 01:59:31,782 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Running jobs are [job_1443082231600_0003] 2015-09-24 02:00:48,025 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 50% complete 2015-09-24 02:00:48,025 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Running jobs are [job_1443082231600_0003] 2015-09-24 02:00:53,055 [main] INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at /0.0.0.0:8032 2015-09-24 02:00:53,104 [main] INFO org.apache.hadoop.mapred.ClientServiceDelegate - Application state is completed. FinalApplicationStatus=SUCCEEDED. Redirecting to job history server 2015-09-24 02:00:58,180 [main] INFO org.apache.hadoop.ipc.Client - Retrying connect to server: 0.0.0.0/0.0.0.0:10020. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2015-09-24 02:00:59,182 [main] INFO org.apache.hadoop.ipc.Client - Retrying connect to server: 0.0.0.0/0.0.0.0:10020. Already tried 1 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) 2015-09-24 02:01:00,185 [main] INFO org.apache.hadoop.ipc.Client - Retrying connect to server: 0.0.0.0/0.0.0.0:10020. Already tried 2 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS) (F,96,86000.0,95105) (M,24,80000.0,95050) (F,84,89000.0,94040) (M,36,85000.0,95101) (F,69,91000.0,95050) (F,96,80000.0,95051) (M,78,87000.0,95105) (M,25,96000.0,95103) (M,89,90000.0,95102) (F,82,77000.0,95051) (M,97,96000.0,95102) (F,39,82000.0,95051) (M,36,79000.0,95101) (M,75,84000.0,95103) (F,78,91000.0,95102) (M,59,77000.0,95051) (F,52,76000.0,95050) (M,52,97000.0,95102) (F,28,98000.0,95105) (M,91,96000.0,94041) (F,47,85000.0,95051) (M,79,85000.0,95101) (F,93,93000.0,95102) (F,33,82000.0,95101) (F,77,96000.0,95103) (F,93,84000.0,95051) (M,23,83000.0,95050) (M,54,97000.0,95101) (F,25,93000.0,94040) (M,52,85000.0,95102) (M,60,78000.0,94040) (F,74,89000.0,94040) (F,23,76000.0,95101) (M,46,93000.0,95051) (F,63,92000.0,95105) (F,86,93000.0,95101) (F,37,95000.0,95101) (M,41,89000.0,95050) (F,89,77000.0,94041) (F,82,84000.0,95050) (M,66,96000.0,95051) 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(F,65,78000.0,94040) (F,74,81000.0,95103) (M,83,97000.0,95101) (M,42,92000.0,95102) (M,82,92000.0,95105) (F,41,91000.0,94041) (F,35,97000.0,94040) (F,46,85000.0,95050) (M,34,86000.0,94041) (F,37,85000.0,94041) (M,64,91000.0,94040) (M,92,84000.0,95051) (M,56,83000.0,95103) (F,68,98000.0,95101) (M,28,81000.0,95050) (F,81,93000.0,95050) (M,71,87000.0,95051) (M,90,86000.0,95050) (F,92,78000.0,94041) (M,42,97000.0,95101) (F,97,83000.0,94041) (M,41,86000.0,95051) (F,96,99000.0,95102) (F,56,96000.0,95051) (F,63,99000.0,95105) (F,69,89000.0,95050) (M,67,85000.0,95105) (M,61,83000.0,95051) (M,86,96000.0,95103) (F,84,82000.0,94041) (M,91,90000.0,95050) (F,36,99000.0,94041) (M,75,97000.0,95105) (M,39,93000.0,95050) (M,56,90000.0,95050) (M,61,91000.0,95105) (M,29,93000.0,94041) (M,79,99000.0,95102) (M,48,91000.0,95101) (F,95,76000.0,95101) (M,47,98000.0,95050) (M,61,88000.0,95101) (M,74,77000.0,95101) (M,75,83000.0,94040) (M,34,82000.0,95103) (M,70,85000.0,95103) (F,43,94000.0,94041) (F,64,91000.0,95105) (F,21,95000.0,95051) (M,55,91000.0,95051) (M,27,85000.0,95105) (F,40,84000.0,94040) (F,41,84000.0,94041) (F,50,87000.0,95051) (M,72,82000.0,95103) (F,50,87000.0,95105) (F,31,93000.0,95102) (F,45,80000.0,95050) (F,62,77000.0,94040) (M,93,91000.0,95101) (M,77,94000.0,95051) (F,33,82000.0,95051) (M,95,87000.0,95105) (M,40,79000.0,95102) (M,82,87000.0,95050) (M,55,85000.0,95051) (M,52,96000.0,95102) (F,52,96000.0,95050) (F,78,82000.0,95102) (F,31,82000.0,94041) (F,60,97000.0,95101) (M,77,81000.0,95102) (F,78,93000.0,95101) (M,74,82000.0,94040) (M,62,77000.0,95050) (F,72,77000.0,95102) (M,96,87000.0,94041) (F,89,93000.0,95051) (M,59,87000.0,95050) (F,26,81000.0,95105) (F,84,77000.0,95051) (F,42,84000.0,94040) (F,59,96000.0,94041) (F,31,78000.0,95050) (F,91,85000.0,95105) (F,87,79000.0,95102) (M,39,88000.0,95105) (F,47,86000.0,95051) (F,24,92000.0,95101) (F,76,85000.0,95103) (F,48,83000.0,95105) (M,50,88000.0,95105) (F,61,93000.0,94041) (F,59,98000.0,95050) (F,57,95000.0,95050) (M,77,76000.0,95105) (M,34,90000.0,95105) (M,23,91000.0,95050) (M,38,88000.0,95051) (F,35,86000.0,95102) (M,27,91000.0,95103) (F,99,78000.0,95051) (F,77,94000.0,94041) (M,23,83000.0,95103) (M,93,91000.0,95051) (F,94,89000.0,95103) (M,99,99000.0,95105) (M,75,84000.0,94040) (M,32,89000.0,94041) (F,57,76000.0,94040) (F,94,95000.0,95103) (M,66,82000.0,94041) (F,56,98000.0,94041) (M,37,88000.0,95105) (M,89,82000.0,95050) (M,91,79000.0,95103) (F,72,90000.0,95102) (F,53,85000.0,95050) (F,87,91000.0,95105) (M,74,91000.0,95050) (F,62,99000.0,95102) (M,46,95000.0,95105) (F,73,78000.0,95050) (F,35,94000.0,95102) (F,60,77000.0,95105) (M,83,93000.0,95105) (F,55,76000.0,95051) (F,36,90000.0,95101) (F,75,87000.0,95103) (F,91,98000.0,95103) (F,66,87000.0,95101) (M,83,91000.0,95103) (M,52,77000.0,94040) (F,76,85000.0,95103) (F,98,78000.0,95102) (F,60,89000.0,95050) (F,30,76000.0,95101) (F,53,95000.0,95050) (M,63,85000.0,95105) (F,25,94000.0,95050) (M,29,98000.0,95103) (M,53,82000.0,95050) (F,70,89000.0,95101) (F,76,83000.0,95105) (M,85,98000.0,95050) (F,81,97000.0,95103) (M,30,77000.0,94041) (F,73,85000.0,95102) (M,94,93000.0,95103) (F,83,80000.0,95101) (F,44,88000.0,94040) (F,35,83000.0,95051) (F,25,82000.0,94040) (M,26,92000.0,95101) (F,60,81000.0,95105) (F,47,78000.0,94040) (F,53,87000.0,94040) (F,44,88000.0,95051) (M,73,96000.0,95103) (F,77,95000.0,95103) (M,24,93000.0,95050) (F,21,76000.0,95050) (F,82,90000.0,95103) (M,71,97000.0,95051) (M,53,79000.0,95105) (M,28,84000.0,94040) (M,35,97000.0,95101) (F,75,76000.0,94040) (M,87,94000.0,94041) (F,89,79000.0,95102) (F,80,92000.0,95102) (M,24,77000.0,95102) (F,40,94000.0,95105) (M,43,80000.0,94041) (M,23,80000.0,94041) (F,51,83000.0,94041) (F,90,78000.0,94040) (F,41,79000.0,95102) (M,48,93000.0,94041) (M,69,94000.0,94040) (F,36,81000.0,95101) (M,35,91000.0,95051) (F,26,88000.0,95050) (M,35,83000.0,94041) (F,36,77000.0,95103) (M,57,91000.0,95103) (F,57,89000.0,95101) (F,38,86000.0,94041) (F,31,83000.0,95050) (M,47,96000.0,94041) (F,91,83000.0,95101) (F,21,78000.0,95103) (M,32,84000.0,95051) (F,41,93000.0,94041) (M,81,93000.0,95102) (F,59,78000.0,95105) (M,71,90000.0,95050) (F,51,77000.0,95051) (M,29,88000.0,95102) (F,40,93000.0,95102) (F,89,99000.0,95105) (F,64,77000.0,95103) (F,53,87000.0,94041) (M,53,97000.0,94040) (M,45,78000.0,94040) (F,76,89000.0,94041) (M,59,81000.0,95050) (F,24,76000.0,94041) (M,72,95000.0,95051) (M,63,83000.0,94040) (F,39,76000.0,94041) (F,26,85000.0,95101) (M,90,99000.0,95102) (F,47,76000.0,95103) (M,72,86000.0,95105) (M,38,92000.0,95050) (M,54,78000.0,95101) (F,48,86000.0,95102) (F,37,78000.0,94040) (F,75,88000.0,95103) (F,66,78000.0,95050) (M,58,80000.0,94040) (M,84,88000.0,95050) (F,35,94000.0,95050) (M,57,88000.0,95102) (M,68,83000.0,95050) (M,37,91000.0,95103) (M,65,79000.0,95101) (M,65,85000.0,95101) (F,97,83000.0,95102) (M,43,83000.0,95051) (F,73,82000.0,95103) (M,89,87000.0,95050) (F,74,84000.0,95103) (M,73,90000.0,94041) (F,46,97000.0,95103) (M,36,82000.0,94041) (M,80,82000.0,95105) (F,78,79000.0,95102) (M,67,96000.0,94040) (F,48,98000.0,95102) (F,82,86000.0,95050) (M,79,80000.0,95050) (M,96,84000.0,95103) (M,51,87000.0,94040) (F,29,84000.0,95051) (M,47,86000.0,94040) (M,54,96000.0,94041) (F,80,94000.0,94041) (F,92,93000.0,95103) (F,59,79000.0,95050) (M,95,80000.0,95050) (M,67,92000.0,94040) (F,23,98000.0,95103) (M,91,82000.0,95051) (M,27,89000.0,95105) (M,43,77000.0,94041) (F,65,83000.0,94040) (F,65,82000.0,95051) (M,43,98000.0,95105) (F,51,86000.0,95102) (M,76,83000.0,95051) (F,25,92000.0,94040) (M,48,76000.0,95102) (F,43,86000.0,95050) (F,57,83000.0,95101) (F,48,84000.0,95051) (M,37,98000.0,95102) (F,98,81000.0,95105) (M,78,86000.0,94041) (F,34,93000.0,95102) (M,53,94000.0,95102) (M,69,98000.0,94040) (F,70,84000.0,94041) (F,89,87000.0,94040) (F,52,89000.0,95102) (F,84,79000.0,95102) (M,44,86000.0,94041) (M,51,93000.0,94041) (M,98,81000.0,95102) (F,82,77000.0,95101) (M,50,82000.0,95103) (F,59,76000.0,95051) (M,29,76000.0,94041) (F,30,81000.0,95051) (F,22,96000.0,95105) (M,64,88000.0,94040) (M,80,78000.0,95102) (F,94,85000.0,95051) (M,63,95000.0,95103) (F,51,78000.0,95050) (M,39,94000.0,95105) (M,80,85000.0,95101) (M,92,89000.0,95102) (M,44,88000.0,95103) (M,57,92000.0,95050) (F,64,94000.0,95051) (F,88,91000.0,95102) (F,43,83000.0,95101) (F,33,93000.0,95050) (M,64,92000.0,95102) (M,91,92000.0,95050) (F,32,88000.0,95105) (M,78,87000.0,94041) (F,64,85000.0,94040) (M,93,96000.0,95102) (F,72,98000.0,95103) (M,68,76000.0,95051) (M,52,95000.0,95050) (F,75,93000.0,95103) (M,45,85000.0,94041) (F,70,98000.0,95051) (F,74,96000.0,95101) (F,81,85000.0,95102) (M,83,91000.0,95105) (M,32,89000.0,95101) (F,58,90000.0,94041) (M,55,80000.0,95050) (F,23,79000.0,95051) (M,91,79000.0,95103) (F,21,98000.0,95102) (F,57,91000.0,95101) (M,58,91000.0,95051) (F,41,94000.0,95101) (M,67,95000.0,94041) (M,69,80000.0,95101) (M,23,77000.0,94041) (F,94,92000.0,95105) (F,60,92000.0,95051) (F,53,84000.0,94041) (F,48,98000.0,95103) (M,70,88000.0,95051) (M,76,94000.0,95103) (F,22,88000.0,94040) (F,80,81000.0,95102) (F,57,80000.0,95051) (F,57,99000.0,95103) (M,50,78000.0,95050) (M,40,81000.0,95050) (F,93,97000.0,95050) (M,40,80000.0,94041) (M,35,91000.0,95101) (F,50,96000.0,94041) (F,27,90000.0,95105) (F,23,91000.0,95105) (M,49,80000.0,94041) (M,90,98000.0,95105) (M,29,91000.0,95050) (F,99,83000.0,95103) (F,43,83000.0,94040) (F,30,90000.0,94041) (F,96,97000.0,95102) (M,83,77000.0,95103) (F,77,97000.0,94040) (F,74,98000.0,95105) (F,96,96000.0,95103) (F,37,81000.0,94041) (M,82,91000.0,94040) (F,33,90000.0,95101) (F,35,86000.0,95102) (F,67,87000.0,95105) (M,95,95000.0,95051) (M,82,95000.0,95101) (F,26,76000.0,95050) (F,65,84000.0,95103) (F,34,91000.0,95102) (F,48,81000.0,94040) (F,93,84000.0,94041) (F,37,79000.0,95105) (M,77,84000.0,95102) (M,94,78000.0,94040) (M,28,79000.0,95051) (F,30,80000.0,94041) (F,54,80000.0,95103) (F,93,96000.0,95105) (F,45,78000.0,94041) right now i'm just executing pig command .I wanna direct or make a copy of output at execution time let it is really difficult to take a snapshot of it. just suggest a solution to overcome from it. the code ILLUSTRATE THE OUTPUT OF THE COMMAND grunt>salaries= load 'salaries' using PigStorage(',') As (gender, age,salary,zip); grunt> salaries= load 'salaries' using PigStorage(',') As (gender:chararray,age:int,salary:double,zip:long); grunt>highsal= filter salaries by salary > 75000; grunt>dump highsal; WHEN THE ABOVE COMMAND EXECUTED THE OUTPUT LISTING ABOVE WIILL BE DISPLAYED . JUST I HAVE COPIED salaries.txt from local FS to hdfs . grunt> store highsal into 'file'; 2015-09-24 02:59:15,981 [main] ERROR org.apache.pig.tools.grunt.Grunt - ERROR 1200: Pig script failed to parse: <line 1, column 6> Undefined alias: highsal Details at logfile: /home/vivek/pig_1443088724224.log grunt> i'm still getting error by suggested query.
You have not defined "highsal" alias when trying to run STORE command. Pig do not store any alias previous session. you have to execute all your command in one session or write a pig script and invoke it. Try like : grunt>salaries= load 'salaries' using PigStorage(',') As (gender, age,salary,zip); grunt> salaries= load 'salaries' using PigStorage(',') As (gender:chararray,age:int,salary:double,zip:long); grunt>highsal= filter salaries by salary > 75000; grunt>STORE highsal INTO 'file'; This will store the "highsal" content in a file name 'file/part-x-xxxxx' on user's HDFS directory. You can also provide HDFS absolute directory path instead of 'file' if you want to wish to store data in directory other than users home directory Hope this helps
store highsal into 'file'; Have a look at apache pig documentation for all commands.
Pig "Max" command for pig-0.12.1 and pig-0.13.0 with Hadoop-2.4.0
I have a pig script I got from Hortonworks that works fine with pig-0.9.2.15 with Hadoop-1.0.3.16. But when I run it with pig-0.12.1(recompiled with -Dhadoopversion=23) or pig-0.13.0 on Hadoop-2.4.0, it won't work. It seems the following line is where the problem is. max_runs = FOREACH grp_data GENERATE group as grp, MAX(runs.runs) as max_runs; Here's the whole script. batting = load 'pig_data/Batting.csv' using PigStorage(','); runs = FOREACH batting GENERATE $0 as playerID, $1 as year, $8 as runs; grp_data = GROUP runs by (year); max_runs = FOREACH grp_data GENERATE group as grp, MAX(runs.runs) as max_runs; join_max_run = JOIN max_runs by ($0, max_runs), runs by (year,runs); join_data = FOREACH join_max_run GENERATE $0 as year, $2 as playerID, $1 as runs; STORE join_data INTO './join_data'; And here's the hadoop error info: 2014-07-29 18:03:02,957 [main] ERROR org.apache.pig.tools.pigstats.PigStats - ERROR 0: org.apache.pig.backend.executionengine.ExecException: ERROR 0: Exception while executing (Name: grp_data: Local Rearrange[tuple]{bytearray}(false) - scope-34 Operator Key: scope-34): org.apache.pig.backend.executionengine.ExecException: ERROR 2106: Error executing an algebraic function 2014-07-29 18:03:02,958 [main] ERROR org.apache.pig.tools.pigstats.mapreduce.MRPigStatsUtil - 1 map reduce job(s) failed! How can I fix this if I still want to use "MAX" function? Thank you! Here's the complete information: 14/07/29 17:50:11 INFO pig.ExecTypeProvider: Trying ExecType : LOCAL 14/07/29 17:50:11 INFO pig.ExecTypeProvider: Trying ExecType : MAPREDUCE 14/07/29 17:50:11 INFO pig.ExecTypeProvider: Picked MAPREDUCE as the ExecType 2014-07-29 17:50:12,104 [main] INFO org.apache.pig.Main - Apache Pig version 0.13.0 (r1606446) compiled Jun 29 2014, 02:27:58 2014-07-29 17:50:12,104 [main] INFO org.apache.pig.Main - Logging error messages to: /root/hadooptestingsuite/scripts/tests/pig_test/hadoop2/pig_1406677812103.log 2014-07-29 17:50:13,050 [main] INFO org.apache.pig.impl.util.Utils - Default bootup file /root/.pigbootup not found 2014-07-29 17:50:13,415 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.job.tracker is deprecated. Instead, use mapreduce.jobtracker.address 2014-07-29 17:50:13,415 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2014-07-29 17:50:13,415 [main] INFO org.apache.pig.backend.hadoop.executionengine.HExecutionEngine - Connecting to hadoop file system at: hdfs://namenode.cmda.hadoop.com:8020 2014-07-29 17:50:14,302 [main] INFO org.apache.pig.backend.hadoop.executionengine.HExecutionEngine - Connecting to map-reduce job tracker at: namenode.cmda.hadoop.com:8021 2014-07-29 17:50:14,990 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2014-07-29 17:50:15,570 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2014-07-29 17:50:15,665 [main] WARN org.apache.pig.newplan.BaseOperatorPlan - Encountered Warning IMPLICIT_CAST_TO_DOUBLE 1 time(s). 2014-07-29 17:50:15,705 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.textoutputformat.separator is deprecated. Instead, use mapreduce.output.textoutputformat.separator 2014-07-29 17:50:15,791 [main] INFO org.apache.pig.tools.pigstats.ScriptState - Pig features used in the script: HASH_JOIN,GROUP_BY 2014-07-29 17:50:15,873 [main] INFO org.apache.pig.newplan.logical.optimizer.LogicalPlanOptimizer - {RULES_ENABLED=[AddForEach, ColumnMapKeyPrune, GroupByConstParallelSetter, LimitOptimizer, LoadTypeCastInserter, MergeFilter, MergeForEach, PartitionFilterOptimizer, PushDownForEachFlatten, PushUpFilter, SplitFilter, StreamTypeCastInserter], RULES_DISABLED=[FilterLogicExpressionSimplifier]} 2014-07-29 17:50:16,319 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler - File concatenation threshold: 100 optimistic? false 2014-07-29 17:50:16,377 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.CombinerOptimizer - Choosing to move algebraic foreach to combiner 2014-07-29 17:50:16,410 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler$LastInputStreamingOptimizer - Rewrite: POPackage->POForEach to POPackage(JoinPackager) 2014-07-29 17:50:16,417 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - MR plan size before optimization: 3 2014-07-29 17:50:16,418 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - Merged 1 map-reduce splittees. 2014-07-29 17:50:16,418 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - Merged 1 out of total 3 MR operators. 2014-07-29 17:50:16,418 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOptimizer - MR plan size after optimization: 2 2014-07-29 17:50:16,493 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2014-07-29 17:50:16,575 [main] INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at namenode.cmda.hadoop.com/10.0.3.1:8050 2014-07-29 17:50:16,973 [main] INFO org.apache.pig.tools.pigstats.mapreduce.MRScriptState - Pig script settings are added to the job 2014-07-29 17:50:17,007 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.job.reduce.markreset.buffer.percent is deprecated. Instead, use mapreduce.reduce.markreset.buffer.percent 2014-07-29 17:50:17,007 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3 2014-07-29 17:50:17,007 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.output.compress is deprecated. Instead, use mapreduce.output.fileoutputformat.compress 2014-07-29 17:50:17,020 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Reduce phase detected, estimating # of required reducers. 2014-07-29 17:50:17,020 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Using reducer estimator: org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.InputSizeReducerEstimator 2014-07-29 17:50:17,064 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.InputSizeReducerEstimator - BytesPerReducer=1000000000 maxReducers=999 totalInputFileSize=6398990 2014-07-29 17:50:17,067 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Setting Parallelism to 1 2014-07-29 17:50:17,067 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.reduce.tasks is deprecated. Instead, use mapreduce.job.reduces 2014-07-29 17:50:17,068 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - This job cannot be converted run in-process 2014-07-29 17:50:17,068 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - creating jar file Job2337803902169382273.jar 2014-07-29 17:50:20,957 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - jar file Job2337803902169382273.jar created 2014-07-29 17:50:20,957 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.jar is deprecated. Instead, use mapreduce.job.jar 2014-07-29 17:50:21,001 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler - Setting up multi store job 2014-07-29 17:50:21,036 [main] INFO org.apache.pig.data.SchemaTupleFrontend - Key [pig.schematuple] is false, will not generate code. 2014-07-29 17:50:21,036 [main] INFO org.apache.pig.data.SchemaTupleFrontend - Starting process to move generated code to distributed cacche 2014-07-29 17:50:21,046 [main] INFO org.apache.pig.data.SchemaTupleFrontend - Setting key [pig.schematuple.classes] with classes to deserialize [] 2014-07-29 17:50:21,310 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 1 map-reduce job(s) waiting for submission. 2014-07-29 17:50:21,311 [main] INFO org.apache.hadoop.conf.Configuration.deprecation - mapred.job.tracker.http.address is deprecated. Instead, use mapreduce.jobtracker.http.address 2014-07-29 17:50:21,332 [JobControl] INFO org.apache.hadoop.yarn.client.RMProxy - Connecting to ResourceManager at namenode.cmda.hadoop.com/10.0.3.1:8050 2014-07-29 17:50:21,366 [JobControl] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2014-07-29 17:50:22,606 [JobControl] INFO org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 1 2014-07-29 17:50:22,606 [JobControl] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1 2014-07-29 17:50:22,629 [JobControl] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths (combined) to process : 1 2014-07-29 17:50:22,729 [JobControl] INFO org.apache.hadoop.mapreduce.JobSubmitter - number of splits:1 2014-07-29 17:50:22,745 [JobControl] INFO org.apache.hadoop.conf.Configuration.deprecation - fs.default.name is deprecated. Instead, use fs.defaultFS 2014-07-29 17:50:23,026 [JobControl] INFO org.apache.hadoop.mapreduce.JobSubmitter - Submitting tokens for job: job_1406677482986_0003 2014-07-29 17:50:23,258 [JobControl] INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl - Submitted application application_1406677482986_0003 2014-07-29 17:50:23,340 [JobControl] INFO org.apache.hadoop.mapreduce.Job - The url to track the job: http://namenode.cmda.hadoop.com:8088/proxy/application_1406677482986_0003/ 2014-07-29 17:50:23,340 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - HadoopJobId: job_1406677482986_0003 2014-07-29 17:50:23,340 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Processing aliases batting,grp_data,max_runs,runs 2014-07-29 17:50:23,340 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - detailed locations: M: batting[3,10],runs[5,7],max_runs[7,11],grp_data[6,11] C: max_runs[7,11],grp_data[6,11] R: max_runs[7,11] 2014-07-29 17:50:23,340 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - More information at: http://namenode.cmda.hadoop.com:50030/jobdetails.jsp?jobid=job_1406677482986_0003 2014-07-29 17:50:23,357 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 0% complete 2014-07-29 17:50:23,357 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Running jobs are [job_1406677482986_0003] 2014-07-29 17:51:15,564 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 50% complete 2014-07-29 17:51:15,564 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Running jobs are [job_1406677482986_0003] 2014-07-29 17:51:18,582 [main] WARN org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Ooops! Some job has failed! Specify -stop_on_failure if you want Pig to stop immediately on failure. 2014-07-29 17:51:18,582 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - job job_1406677482986_0003 has failed! Stop running all dependent jobs 2014-07-29 17:51:18,582 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - 100% complete 2014-07-29 17:51:18,825 [main] ERROR org.apache.pig.tools.pigstats.PigStats - ERROR 0: org.apache.pig.backend.executionengine.ExecException: ERROR 0: Exception while executing (Name: grp_data: Local Rearrange[tuple]{bytearray}(false) - scope-73 Operator Key: scope-73): org.apache.pig.backend.executionengine.ExecException: ERROR 2106: Error executing an algebraic function 2014-07-29 17:51:18,825 [main] ERROR org.apache.pig.tools.pigstats.mapreduce.MRPigStatsUtil - 1 map reduce job(s) failed! 2014-07-29 17:51:18,826 [main] INFO org.apache.pig.tools.pigstats.mapreduce.SimplePigStats - Script Statistics: HadoopVersion PigVersion UserId StartedAt FinishedAt Features 2.4.0 0.13.0 root 2014-07-29 17:50:16 2014-07-29 17:51:18 HASH_JOIN,GROUP_BY Failed! Failed Jobs: JobId Alias Feature Message Outputs job_1406677482986_0003 batting,grp_data,max_runs,runs MULTI_QUERY,COMBINER Message: Job failed! Input(s): Failed to read data from "hdfs://namenode.cmda.hadoop.com:8020/user/root/pig_data/Batting.csv" Output(s): Counters: Total records written : 0 Total bytes written : 0 Spillable Memory Manager spill count : 0 Total bags proactively spilled: 0 Total records proactively spilled: 0 Job DAG: job_1406677482986_0003 -> null, null 2014-07-29 17:51:18,826 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Failed! 2014-07-29 17:51:18,827 [main] ERROR org.apache.pig.tools.grunt.GruntParser - ERROR 2106: Error executing an algebraic function Details at logfile: /root/hadooptestingsuite/scripts/tests/pig_test/hadoop2/pig_1406677812103.log 2014-07-29 17:51:18,828 [main] ERROR org.apache.pig.tools.grunt.GruntParser - ERROR 2244: Job scope-58 failed, hadoop does not return any error message Details at logfile: /root/hadooptestingsuite/scripts/tests/pig_test/hadoop2/pig_1406677812103.log
try by casting MAX function max_runs = FOREACH grp_data GENERATE group as grp, (int)MAX(runs.runs) as max_runs; hope it will work
You should use data types in your load statement. runs = FOREACH batting GENERATE $0 as playerID:chararray, $1 as year:int, $8 as runs:int; If this doesn't help for some reason, try explicit casting. max_runs = FOREACH grp_data GENERATE group as grp, MAX((int)runs.runs) as max_runs;
Thank both #BigData and #Mikko Kupsu for the hint. The issue does indeed have something to do the datatype casting. After specifying the data type of each column as follows everything runs great. batting = LOAD '/user/root/pig_data/Batting.csv' USING PigStorage(',') AS (playerID: CHARARRAY, yearID: INT, stint: INT, teamID: CHARARRAY, lgID: CHARARRAY, G: INT, G_batting: INT, AB: INT, R: INT, H: INT, two_B: INT, three_B: INT, HR: INT, RBI: INT, SB: INT, CS: INT, BB:INT, SO: INT, IBB: INT, HBP: INT, SH: INT, SF: INT, GIDP: INT, G_old: INT);
Pig - Replicated Join
I have two input files Student file : abc 30 4.5 xyz 34 9.5 def 28 6.5 klm 35 10.5 Location file : abc hawthorne xyz artesia def garnet klm vanness My desired ouput abc hawthorne xyz artesia def garnet klm vanness To achieve this, I wrote the following pig program. A = LOAD '/user/hive/warehouse/students.txt' USING PigStorage(' ') AS (NAME:CHARARRAY,AGE:INT,GPA:FLOAT); B = LOAD '/user/hive/warehouse/location.txt.txt' using PigStorage(' ') AS (NAME:CHARARRAY,LOCATION:CHARARRAY); C = JOIN A BY NAME , B BY LOCATION USING 'replicated'; DUMP C; The trouble is that I dont see any output message. On top of that, I see the following warnings while execution : 2014-01-22 15:18:15,829 [main] WARN org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Encountered Warning ACCESSING_NON_EXISTENT_FIELD 2 time(s). 2014-01-22 15:18:15,829 [main] WARN org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Encountered Warning ACCESSING_NON_EXISTENT_FIELD 2 time(s). 2014-01-22 15:18:15,829 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success! 2014-01-22 15:18:15,829 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher - Success! 2014-01-22 15:18:15,832 [main] INFO org.apache.pig.data.SchemaTupleBackend - Key [pig.schematuple] was not set... will not generate code. 2014-01-22 15:18:15,832 [main] INFO org.apache.pig.data.SchemaTupleBackend - Key [pig.schematuple] was not set... will not generate code. 2014-01-22 15:18:15,841 [main] INFO org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 1 2014-01-22 15:18:15,841 [main] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1 2014-01-22 15:18:15,841 [main] INFO org.apache.pig.backend.hadoop.executionengine.util.MapRedUtil - Total input paths to process : 1 Hadoop Job IDs executed by Pig: job_201401210934_0082,job_201401210934_0083
i feel you are not seeing any output because join is not leading to any match. You are creating a join on NAME from A (abc, xyz, def, klm) & LOCATION from B (hawthorne, artesia, garnet, vanness) and if you see there are no matching strings in two data sets, so leading to no join.