Pig 开发手册

oss://${AccessKeyId}:${AccessKeySecret}@${bucket}.${endpoint}/${path}

• ${accessKeyId}：您账号的AccessKeyId。

• ${accessKeySecret}：该AccessKeyId对应的密钥。

• ${bucket}： 该AccessKeyId对应的bucket。

• ${endpoint}：访问OSS使用的网络，由您集群所在的region决定，对应的OSS也需要是在集群对应的region。

  具体的值请参见OSS Endpoint。

• ${path}：bucket中的路径。

1. 编写脚本
   根据准备工作中所上传的OSS路径，修改脚本中的jar包文件路径和输入输出路径。如下所示，注意OSS路径设置形式为oss://${accesskeyId}:${accessKeySecret}@${bucket}.${endpoint}/object/path。

   /*
    * Licensed to the Apache Software Foundation (ASF) under one
   * or more contributor license agreements.  See the NOTICE file
   * distributed with this work for additional information
   * regarding copyright ownership.  The ASF licenses this file
   * to you under the Apache License, Version 2.0 (the
   * "License"); you may not use this file except in compliance
   * with the License.  You may obtain a copy of the License at
   *
   *     http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
   -- 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://${AccessKeyId}:${AccessKeySecret}@${bucket}.${endpoint}/data/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://${AccessKeyId}:${AccessKeySecret}@${bucket}.${endpoint}/data/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, $4 as mean;
   -- Use the  FILTER command to move all records with a score less than or equal to 2.0.
   filtered_uniq_frequency = FILTER uniq_frequency3 BY score > 2.0;
   -- Use the  ORDER command to sort the remaining records by hour and score.
   ordered_uniq_frequency = ORDER filtered_uniq_frequency BY hour, score;
   -- Use the  PigStorage function to store the results.
   -- Output: (hour, n-gram, score, count, average_counts_among_all_hours)
   STORE ordered_uniq_frequency INTO 'oss://${AccessKeyId}:${AccessKeySecret}@${bucket}.${endpoint}/data/script1-hadoop-results' USING PigStorage();

2. 创建作业
   将步骤1中编写的脚本存放到OSS上，假设存储路径为 oss://emr/jars/script1-hadoop.pig，在E-MapReduce作业中创建如下作业。
3. 创建执行计划并运行

   在E-MapReduce执行计划中创建执行计划，将上一步创建好的Pig作业添加到执行计划中，策略请选择运行，script1-hadoop作业就会在选定集群中运行起来。