Metadata-Version: 1.1
Name: apiarist
Version: 0.1.1
Summary: Python Hive query framework
Home-page: http://github.com/msharp/apiarist
Author: Max Sharples
Author-email: maxsharples@gmail.com
License: Apache
Description: # Apiarist
        
        A python 2.5+ package for defining Hive queries which can be run on AWS EMR.
        
        It is, in its current form, only addressing a very narrow use-case. 
        Reading large text files into a Hive database, running a Hive query, and outputting the results to a text file.
        
        File format can be CSV or similar - other delimiters can be specified.
        
        The jobs are runnable locally, which is mainly for testing. You will need a local version of Hive which is in your `PATH` such that the command `hive -f /some/hive/script.hql` causes hive to execute the contents of the file.
        
        It is heavily modeled on [mrjob](https://github.com/Yelp/mrjob) and attempts to present a similar API and use similar common variables to cooperate with `boto`.
        
        ## A simple Hive job
        
        You will need to provide four methods: 
        
          - `table` the name of the table that your query will select from.
          - `input_columns` the columns in the source data file.
          - `output_columns` the columns that your query will output.
          - `query` the HiveQL query.
        
        This code lives in `/examples`.
        
        ```python
        from apiarist.job import HiveJob
        
        class EmailRecipientsSummary(HiveJob):
        
            def table(self):
                return 'emails_sent'
        
            def input_columns(self):
                return [
                        ('day', 'STRING'),
                        ('weekday', 'INT'),
                        ('sent', 'BIGINT')
                        ]
        
            def output_columns(self):
                return [
                        ('year', 'INT'),
                        ('weekday', 'INT'),
                        ('sent', 'BIGINT')
                        ]
        
            def query(self):
                return "SELECT YEAR(day), weekday, SUM(sent) FROM emails_sent GROUP BY YEAR(day), weekday;"
        
        if __name__ == "__main__":
            EmailRecipientsSummary().run()
        ```
        
        ### Try it out
        
        Locally (must have a Hive server available):
        
            python email_recipients_summary.py -r local /path/to/your/local/file.csv
        
        EMR:
        
            python email_recipients_summary.py -r emr s3://path/to/your/S3/files/
        
        *NOTE: for the EMR command, you will need to supply some basic configuration.*
        
        ### Serde
        
        Hive allows custom a serde to be used to define data formats in tables. Apiarist uses [csv-serde](https://github.com/ogrodnek/csv-serde) to handle the CSV format properly.
        
        This serde also allows configuration of the delimiter, quoting character, and escape character. The defaults are, delimiter = `,`, quote character = `"`, escape character = `\`. 
        
        You can override the defaults in your job. You should be careful about escape sequences when doing so because the value needs to be written into a file.
        
        It is best to definie them as string literals. Example:
        
        ```python
        from apiarist.job import HiveJob
        
        class EmailRecipientsSummary(HiveJob):
        
            INFILE_DELIMITER_CHAR = r'\t'
            INFILE_QUOTE_CHAR = r"\'"
            INFILE_ESCAPE_CHAR = r'%'
        
            OUTFILE_DELIMITER_CHAR = r'\t'
            OUTFILE_QUOTE_CHAR = r'\"'
            OUTFILE_ESCAPE_CHAR = r"\\"
        ```
        
        ## Configuration
         
        There are a range of options for providing job-specific configuration.
        
        ### Command-line options
        
        Arguments can be passed to jobs on the command line, or programmatically with an array of options. Argument handling uses the [optparse](https://docs.python.org/2/library/optparse.html) module.
        
        Various options can be passed to control the running of the job. In particular the AWS/EMR options.
        
          - `-r` the run mode. Either `local` or `emr` (default is `local`)
          - `--conf-path` use a YAML configuration file.
          - `--output-dir` where the results of the job will go.
          - `--s3-scratch-uri` the bucket in which all the temporary files can go.
          - `--local-scratch-dir` this is where temporary file will be written.
          - `--s3-log-uri` write the logs to this location on S3.
          - `--ec2-instance-type` the base instance type. Default is `m3.xlarge`
          - `--ec2-master-instance-type` if you want the master type to be different.
          - `--num-ec2-instances` number of instances (including the master). Default is `2`.
          - `--ami-version` the ami version. Default is `latest`.
          - `--hive-version`. Default is `latest`.
          - `--s3-sync-wait-time` to configure how long to wait after uploading files to S3.
          - `--check-emr-status-every` configure the interval between each status check on a running job.
          - `--quiet` less logging
          - `--verbose` more logging
        
        ### Configuration file
        
        You can supply arguments to your job in a configuration file. It takes the same format as `mrjob` configuration.
        
        The name of the arguments is different, using underscores instead of hyphens and omitting leading hyphens.
        Config options are divided by the type of runner (local/emr) to allow provision of all options for a job in one file.
        
        Below is a sample config file:
        
        ```yaml
        runners:
          emr:
            aws_access_key_id: AABBCCDDEEFF11223344
            aws_secret_access_key: AABBCCDDEEFF1122334AABBCCDDEEFF
            ec2_master_instance_type: c1.medium
            ec2_instance_type: m3.xlarge
            num_ec2_instances: 5
            s3_scratch_uri: s3://myjobs/scratchspace/
            hive_version: 0.11.3
          local:
            local_scratch_dir: /home/apiarist/temp/
        ```
        
        Arguments supplied on command-line or in application code will override those supplied in the config file.
        
        ### Environment variables
        
        Some environment variables are used when the value is not provided in other configuration methods.
        
        `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` for connecting to AWS.
        
        `S3_SCRATCH_URI` a S3 base location where all the temporary file for the job will be written. 
        
        `APIARIST_TMP_DIR` where local files will be written during job runs. (This is overridden by the `--local-scratch-dir` option)
        
        `CSV_SERDE_JAR_S3` a permanent location of the serde jar. If this is not set, Apiarist will automatically upload a copy of the jar to an S3 location in the scratch space.
        
        ### Passing options to your jobs
        
        Jobs can be configured to accept arguments. 
        
        To do this, add the following method to your job class to configutr the options:
        
        ```python
        def configure_options(self):
            super(EmailRecipientsSummary, self).configure_options()
            self.add_passthrough_option('--year', dest='year')
        ```
        
        And then use the option by providing it in the command line arguments, like this:
        
            python email_recipients_summary.py -r local /path/to/your/local/file.csv --year 2014
        
        Then incorporating it into your HiveQL query like this:
        
        ```python
        def query(self):
            q = "SELECT YEAR(day), weekday, SUM(sent) "
            q += "FROM emails_sent "
            q += "WHERE YEAR(day) = {0} ".format(self.options.year)
            q += "GROUP BY YEAR(day), weekday;"
            return q
        ```
        
        ## License
        
        Apiarist source code is released under Apache 2 License. Check LICENSE file for more information.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.5
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: System :: Distributed Computing
Provides: apiarist
