This topic describes how to configure a Pig job.


  • A project is created. For more information, see Manage projects.
  • A Pig script is available. Sample code:
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     -- Query Phrase Popularity (Hadoop cluster)
     -- This script processes a search query log file from the Excite search engine and finds search phrases that occur with particular high frequency during certain times of the day. 
     -- Register the tutorial JAR file so that the included UDFs can be called in the script.
     REGISTER oss://emr/checklist/jars/chengtao/pig/tutorial.jar;
     -- Use the PigStorage function to load the excite log file into the "raw" bag as an array of records.
     -- Input: (user,time,query) 
     raw = LOAD 'oss://emr/checklist/data/chengtao/pig/excite.log.bz2' USING PigStorage('\t') AS (user, time, query);
     -- Call the NonURLDetector UDF to remove records if the query field is empty or a URL. 
     clean1 = FILTER raw BY org.apache.pig.tutorial.NonURLDetector(query);
     -- Call the ToLower UDF to change the query field to lowercase. 
     clean2 = FOREACH clean1 GENERATE user, time, org.apache.pig.tutorial.ToLower(query) as query;
     -- Because the log file only contains queries for a single day, we are only interested in the hour.
     -- The excite query log timestamp format is YYMMDDHHMMSS.
     -- Call the ExtractHour UDF to extract the hour (HH) from the time field.
     houred = FOREACH clean2 GENERATE user, org.apache.pig.tutorial.ExtractHour(time) as hour, query;
     -- Call the NGramGenerator UDF to compose the n-grams of the query.
     ngramed1 = FOREACH houred GENERATE user, hour, flatten(org.apache.pig.tutorial.NGramGenerator(query)) as ngram;
     -- Use the DISTINCT command to get the unique n-grams for all records.
     ngramed2 = DISTINCT ngramed1;
     -- Use the GROUP command to group records by n-gram and hour. 
     hour_frequency1 = GROUP ngramed2 BY (ngram, hour);
     -- Use the COUNT function to get the count (occurrences) of each n-gram. 
     hour_frequency2 = FOREACH hour_frequency1 GENERATE flatten($0), COUNT($1) as count;
     -- Use the GROUP command to group records by n-gram only. 
     -- Each group now corresponds to a distinct n-gram and has the count for each hour.
     uniq_frequency1 = GROUP hour_frequency2 BY group::ngram;
     -- For each group, identify the hour in which this n-gram is used with a particularly high frequency.
     -- Call the ScoreGenerator UDF to calculate a "popularity" score for the n-gram.
     uniq_frequency2 = FOREACH uniq_frequency1 GENERATE flatten($0), flatten(org.apache.pig.tutorial.ScoreGenerator($1));
     -- Use the FOREACH-GENERATE command to assign names to the fields. 
     uniq_frequency3 = FOREACH uniq_frequency2 GENERATE $1 as hour, $0 as ngram, $2 as score, $3 as count, $4 as mean;
     -- Use the FILTER command to move all records with a score less than or equal to 2.0.
     filtered_uniq_frequency = FILTER uniq_frequency3 BY score > 2.0;
     -- Use the ORDER command to sort the remaining records by hour and score. 
     ordered_uniq_frequency = ORDER filtered_uniq_frequency BY hour, score;
     -- Use the PigStorage function to store the results. 
     -- Output: (hour, n-gram, score, count, average_counts_among_all_hours)
     STORE ordered_uniq_frequency INTO 'oss://emr/checklist/data/chengtao/pig/script1-hadoop-results' USING PigStorage();
  • The script1-hadoop-oss.pig file is saved and uploaded to a directory in OSS, such as oss://path/to/script1-hadoop-oss.pig.


  1. Log on to the Alibaba Cloud E-MapReduce console with an Alibaba Cloud account.
  2. Click the Data Platform tab.
  3. In the Projects section, click Edit Job in the row of a project.
  4. In the left-side navigation pane, right-click the required folder and choose Create Job from the shortcut menu.
    Note You can also right-click the folder to create a subfolder, rename the folder, or delete the folder.
  5. In the dialog box that appears, set the Name and Description parameters, and select Pig from the Job Type drop-down list.
    This option indicates that a Pig job will be created. You can use the following command syntax to submit a Pig job:
    pig [user provided parameters]
  6. Click OK.
  7. Specify the command line arguments required to submit the job in the Content field.
    For example, to use the Pig script uploaded to OSS, enter the following command:
    -x mapreduce ossref://emr/checklist/jars/chengtao/pig/script1-hadoop-oss.pig
    Note Click Enter an OSS path in the lower part of the page. In the dialog box that appears, set File Prefix to OSSREF and specify the file in File Path. The system automatically completes the path of the Pig script in OSS.
  8. Click Save.