ElasticSearch Import Utility (esimport)
================================

Tool exists to index content from a CSV in ElasticSearch.

Use
---

To index the contents of a CSV file (where the first row contains field
names) into an ElasticSearch server, you must supply the -s, -f, -i and
-t arguments. If the specified index or type does not exist within the
specified ElasticSearch server, it will be created when the module
executes. The following example will index data from data.file into
ElasticSearch at http://myserver:9200/myindex/mytype:

.. code:: Bash

    python -m esimport -s myserver:9200 -f /path/to/import/data.file -i myindex -t mytype

-  -s *server* (may either be a hostname:port or fully qualified, i.e.
   https://servername:port)
-  -f *filepath* (location of tab-delimited file to import data from)
-  -i *index*\ name\_ (name of the target index within ElasticSearch)
-  -t *type*\ name\_ (name of the target document type within
   ElasticSearch)

Further help available via the script:

.. code:: Bash

    python -m esimport --help

Additional Options
~~~~~~~~~~~~~~~~~~

Custom Delimiter
^^^^^^^^^^^^^^^^

The default delimiter for the operation is a ",", but you may specify different delimiters via the -d argument.

.. code:: Bash

    python -m esimport -s myserver:9200 -f /path/to/import/data.file -i myindex -t mytype -d '|'

- -d *delimiter* (the delimiter separating columns within the CSV)

Clear Existing Data First
^^^^^^^^^^^^^^^^^^^^^^^^^

When indexing data in ElasticSearch, you may optionally clear the
existing ElasticSearch type before data is added by including the -rm
argument.

.. code:: Bash

    python -m esimport -s myserver:9200 -f /path/to/import/data.file -i myindex -t mytype -rm

-  -rm (removes all documents of given type within the specified index
   on ElasticSearch)

Mapping
^^^^^^^

Mapping is the definitiion of the field names and value types of a
document indexed within ElasticSearch. Characteristics such as field
type, whether a field is searchable, and whether to include a timestamp
may all be defined in a map.

*Please note:* If the specified mapping does not match the field names
in the tab-delimited file, you should supply a field translation file
(described below).

A mapping file can be specified by adding the -m parameter to the
command:

.. code:: Bash

    python -m esimport -s myserver:9200 -f /path/to/import/data.file -i myindex -t mytype -m /path/to/mapping.json

-  -m *mapping*\ filepath\_ (location of JSON formatted mapping file for
   specified type)

Maps should be provided in JSON format, as seen below and on the
ElasticSearch website.

Sample mapping for a document type "tracks"
'''''''''''''''''''''''''''''''''''''''''''

.. code:: JSON

    {
        "tracks" : {
            "properties" : {
                "genre" : {
                    "type" : "string"
                },
                "album" : {
                    "type" : "string"
                },
                "ISRC" : {
                    "type" : "string"
                },
                "recordCompany" : {
                    "type" : "string"
                },
                "artist" : {
                    "type" : "string"
                },
                "songToken" : {
                    "type" : "integer"
                },
                "durationInSeconds" : {
                    "type" : "integer"
                },
                "title" : {
                    "type" : "string"
                }
            }
        }
    }

More details on mapping may be found in `ElasticSearch's mapping
reference <http://www.elasticsearch.org/guide/reference/mapping/>`__.

Field Translations
^^^^^^^^^^^^^^^^^^

If the original field names from the CSV file need to be altered or
filtered during the import, you may provide a field translations file.
The first row of this file should consist of the original field names,
separated by the specified delimiter; the second, the new names, again
separated by the specified delimeter.

*Please note:* Any original field names omitted from the first row, will
be omitted from the indexed data as well. This is a handy way to filter
the columns at time of indexing if that is necessary.

.. code:: Bash

    python -m esimport -s myserver:9200 -f /path/to/import/data.file -i myindex -t mytype -rm -m /path/to/mapping.json -n /path/to/field/name/translations.file

-  -n *field*\ translation\_filepath\_ (location of CSV field
   translation file for specified type)

Sample Field Name Translations File
'''''''''''''''''''''''''''''''''''

::

    Album_Category,Album_ID,ISRC,Record_Co,Song_Artist,Song_ID,Song_Secs,Song_Title
    genre,albumID,ISRC,recordCompany,artist,songID,duration,title

Basic Auth
^^^^^^^^^^

If login credentials are required, add the arguments -user and -pass

.. code:: Bash

    python -m esimport -s https://myserver.com -f /path/to/import/data.file -i myindex -t mytype -user exampleuser -pass examplepassword

Verify SSL
^^^^^^^^^^

If ElasticSearch requires SSL, the -nv setting can be used to bypass certificate verification if necessary.

.. code:: Bash

    python -m esimport -s https://myserver.com -f /path/to/import/data.file -i myindex -t mytype -user exampleuser -pass examplepassword -nv

Bulk Index Count
^^^^^^^^^^^^^^^^

You may specify the max number of records to index at time (defaults to 1000) by using the `-bc` argument.

.. code:: Bash

    python -m esimport -s https://myserver.com -f /path/to/import/data.file -i myindex -t mytype -user exampleuser -pass examplepassword -bc 500

Dependencies
------------

-  Python libraries

   -  ``rawes``: `Github <https://github.com/humangeo/rawes>`__ \|
      `documentation <https://github.com/humangeo/rawes#rawes>`__

-  ElasticSearch

