luigi学习2-在hadoop上运行Top Artists

一、AggregateArtistsHadoop

class AggregateArtistsHadoop(luigi.contrib.hadoop.JobTask):
    date_interval = luigi.DateIntervalParameter()

    def output(self):
        return luigi.contrib.hdfs.HdfsTarget("data/artist_streams_%s.tsv" % self.date_interval)

    def requires(self):
        return [StreamsHdfs(date) for date in self.date_interval]

    def mapper(self, line):
        timestamp, artist, track = line.strip().split()
        yield artist, 1

    def reducer(self, key, values):
        yield key, sum(values)

实现的功能和AggregateArtists类似，需要注意的是：

luigi.contrib.hadoop.JobTask不需要你实现run方法，需要你实现mapper和reducer方法。mapper和combiner需要yield包含两个元素的tuple，这两个元素也可以是tuple类型的。

这个task是依赖StreamsHdfs类型task的。现在看看StreamsHdfs的内容吧：

二、StreamHdfs

class StreamsHdfs(Streams):
    def output(self):
        return luigi.contrib.hdfs.HdfsTarget(self.date.strftime(‘data/streams_%Y_%m_%d_faked.tsv‘))

这个类和Stream类的工作是一样的，所以它继承了Stream类，并且重写了output方法，也就是说这个类最终的结果输出是在hdfs上。

三、执行AggregateArtistsHadoop

执行下面的命令，出现了报错，从错误信息中，我们可以看到NoSectionError，这是关于配置文件的错误，详情请参考luigi的配置文件，我的博客也给出了部分常用的配置

 PYTHONPATH=‘‘ luigi --module top_artists AggregateArtistsHadoop --local-scheduler --date-interval 2012-06

  File "/root/miniconda2/envs/my_python_env/lib/python2.7/site-packages/luigi/configuration.py", line 103, in get
    return self._get_with_default(ConfigParser.get, section, option, default, **kwargs)
  File "/root/miniconda2/envs/my_python_env/lib/python2.7/site-packages/luigi/configuration.py", line 93, in _get_with_default
    return method(self, section, option, **kwargs)
  File "/root/miniconda2/envs/my_python_env/lib/python2.7/ConfigParser.py", line 607, in get
    raise NoSectionError(section)
NoSectionError: No section: ‘hadoop‘
Exception AttributeError: "‘DefaultHadoopJobRunner‘ object has no attribute ‘tmp_dir‘" in <bound method DefaultHadoopJobRunner.__del__ of <luigi.contrib.hadoop.DefaultHadoopJobRunner object at 0x7fda9c9b38d0>> ignored

在当前工作目录创建luigi.cfg，并且写入下面的配置，然后重新执行该命令

(my_python_env)[[email protected] pythonCode]# cat luigi.cfg
[hadoop]
command=hadoop#提交hadoop作业的命令
python-executable=python#本机执行python脚本的命令
scheduler=fair#hadoop的调度器
streaming-jar=/usr/local/hadoop-2.6.0/share/hadoop/tools/lib/hadoop-streaming-2.6.0.jar#streaming包的位置
version=apache1#hadoop的版本

四、find top Artists

如果你看到了这里，说明已经计算出了每个artist的出现次数，并且保存在本地或者HDFS上的文件中。现在我们将要找出前10个artist。这里我们选用普通的python程序来计算。

class Top10Artists(luigi.Task):
    date_interval = luigi.DateIntervalParameter()
    use_hadoop = luigi.BoolParameter()

    def requires(self):
        if self.use_hadoop:
            return AggregateArtistsHadoop(self.date_interval)
        else:
            return AggregateArtists(self.date_interval)

    def output(self):
        return luigi.LocalTarget("data/top_artists_%s.tsv" % self.date_interval)

    def run(self):
        top_10 = nlargest(10, self._input_iterator())
        with self.output().open(‘w‘) as out_file:
            for streams, artist in top_10:
                print >> out_file, self.date_interval.date_a, self.date_interval.date_b, artist, streams

    def _input_iterator(self):
        with self.input().open(‘r‘) as in_file:
            for line in in_file:
                artist, streams = line.strip().split()
                yield int(streams), int(artist)

运行下面命令，来完成top10的计算

PYTHONPATH=‘‘ luigi --module top_artists Top10Artists  --local-scheduler --date-interval 2012-06

最终会在data目录下产生新的文件：

(my_python_env)[[email protected] pythonCode]# ls data/
artist_streams_2012-06.tsv    streams_2012_06_06_faked.tsv  streams_2012_06_12_faked.tsv  streams_2012_06_18_faked.tsv  streams_2012_06_24_faked.tsv  streams_2012_06_30_faked.tsv
streams_2012_06_01_faked.tsv  streams_2012_06_07_faked.tsv  streams_2012_06_13_faked.tsv  streams_2012_06_19_faked.tsv  streams_2012_06_25_faked.tsv  top_artists_2012-06.tsv
streams_2012_06_02_faked.tsv  streams_2012_06_08_faked.tsv  streams_2012_06_14_faked.tsv  streams_2012_06_20_faked.tsv  streams_2012_06_26_faked.tsv
streams_2012_06_03_faked.tsv  streams_2012_06_09_faked.tsv  streams_2012_06_15_faked.tsv  streams_2012_06_21_faked.tsv  streams_2012_06_27_faked.tsv
streams_2012_06_04_faked.tsv  streams_2012_06_10_faked.tsv  streams_2012_06_16_faked.tsv  streams_2012_06_22_faked.tsv  streams_2012_06_28_faked.tsv
streams_2012_06_05_faked.tsv  streams_2012_06_11_faked.tsv  streams_2012_06_17_faked.tsv  streams_2012_06_23_faked.tsv  streams_2012_06_29_faked.tsv
(my_python_env)[[email protected] pythonCode]# cat data/top_artists_2012-06.tsv
2012-06-01    2012-07-01    858    47
2012-06-01    2012-07-01    594    47
2012-06-01    2012-07-01    248    47
2012-06-01    2012-07-01    164    46
2012-06-01    2012-07-01    846    45
2012-06-01    2012-07-01    776    44
2012-06-01    2012-07-01    75    44
2012-06-01    2012-07-01    345    44
2012-06-01    2012-07-01    195    44
2012-06-01    2012-07-01    750    43

五、将top10插入到msyql中

class ArtistToplistToMysql(luigi.Task):
    date_interval = luigi.DateIntervalParameter()
    use_hadoop = luigi.BoolParameter()

    def requires(self):
        return Top10Artists(self.date_interval,self.use_hadoop)

    def run(self):
        conn = MySQLdb.connect(host=‘localhost‘, port=3306, user=‘root‘, passwd=‘123456‘, db=‘test‘,charset=‘utf8‘, use_unicode=False)
        cursor = conn.cursor()
        with self.input().open(‘r‘) as in_file:
            for line in in_file:
                start_date,end_date,artist,count = line.strip().split()
                insert_sql = "insert into artist (startdate,enddate,artist,score) values(‘%s‘,‘%s‘,‘%s‘,‘%d‘)" % (start_date , end_date, artist, int(count))
                cursor.execute(insert_sql)
        conn.commit()
        conn.close()

执行下面的命令来完成插入：

PYTHONPATH=‘‘ luigi --module top_artists ArtistToplistToMysql  --local-scheduler --date-interval 2012-06

完成之后查看数据库内容：

所有的任务到此已经完成了调试