The CKAN DataStore provides a database for structured storage of data together with a powerful Web-accessible Data API, all seamlessly integrated into the CKAN interface and authorization system.
Warning
Make sure that you follow the steps below and make sure that the settings are correct. Wrong settings could lead to serious security issues.
The DataStore in previous lives required a custom setup of ElasticSearch and Nginx, but that is no more, as it the relational database management system PostgreSQL. However, you should set-up a separate database for the datastore and create a read-only user to make your CKAN installation save.
In your config file ensure that the datastore extension is enabled:
ckan.plugins = datastoreAlso ensure that the ckan.datastore.write_url and datastore.read_url variables are set:
ckan.datastore.write_url = postgresql://ckanuser:pass@localhost/datastore
ckan.datastore.read_url = postgresql://readonlyuser:pass@localhost/datastoreA few things have to be kept in mind
- The datastore cannot be on the CKAN database (except for testing)
- The write user (i.e.
ckanuser) and read-only user (i.e.readonlyuser) cannot be the same
To create a new database and a read-only user, use the provided paster commands after you have set the right database URLs.:
paster --plugin=ckan datastore create-db SQL_SUPER_USER
paster --plugin=ckan datastore create-read-only-user SQL_SUPER_USERTo test the setup you can create a new datastore, so on linux command line do:
curl -X POST http://127.0.0.1:5000/api/3/action/datastore_create -H "Authorization: {YOUR-API-KEY}" -d '{"resource_id": "{RESOURCE-ID}", "fields": [ {"id": "a"}, {"id": "b"} ], "records": [ { "a": 1, "b": "xyz"}, {"a": 2, "b": "zzz"} ]}'The DataStore is distinct but complementary to the FileStore (see filestore). In contrast to the the FileStore which provides 'blob' storage of whole files with no way to access or query parts of that file, the DataStore is like a database in which individual data elements are accessible and queryable. To illustrate this distinction consider storing a spreadsheet file like a CSV or Excel document. In the FileStore this filed would be stored directly. To access it you would download the file as a whole. By contrast, if the spreadsheet data is stored in the DataStore one would be able to access individual spreadsheet rows via a simple web-api as well as being able to make queries over the spreadsheet contents.
Often, one wants data that is added to CKAN (whether it is linked to or uploaded to the FileStore <filestore>) to be automatically added to the DataStore. This requires some processing, to extract the data from your files and to add it to the DataStore in the format the DataStore can handle.
This task of automatically parsing and then adding data to the datastore is performed by a DataStorer, a queue process that runs asynchronously and can be triggered by uploads or other activities. The DataStorer is an extension and can be found, along with installation instructions, at: https://github.com/okfn/ckanext-datastorer
The DataStore's Data API, which derives from the underlying data-table, is RESTful and JSON-based with extensive query capabilities.
Each resource in a CKAN instance can have an associated DataStore 'table'. The basic API for accessing the DataStore is detailed below. For a detailed tutorial on using this API see using-data-api.
Note
Lists can always be expressed in different ways. It is possible to use lists, comma separated strings or single items. These are valid lists: ['foo', 'bar'], foo, bar, "foo", "bar" and foo.
The datastore_create API endpoint allows a user to post JSON data to be stored against a resource. This endpoint also supports altering tables, aliases and indexes and bulk insertion. The JSON must be in the following form:
{
resource_id: resource_id, # the data is going to be stored against.
aliases: # list of names for read only aliases to the resource
fields: [] # a list of dictionaries of fields/columns and their extra metadata.
records: [] # a list of dictionaries of the data, eg: [{"dob": "2005", "some_stuff": ['a', b']}, ..]
primary_key: # list of fields that represent a unique key
indexes: # indexes on table
}See fields and records for details on how to lay out records.
The datastore_delete API endpoint allows a user to delete from a resource. The JSON for searching must be in the following form:
{
resource_id: resource_id # the data that is going to be deleted.
filter: # dictionary of matching conditions to delete
# e.g {'key1': 'a. 'key2': 'b'}
# this will be equivalent to "delete from table where key1 = 'a' and key2 = 'b' "
}The datastore_upsert API endpoint allows a user to add data to an existing datastore resource. In order for the upsert and update to work a unique key has to defined via the datastore_create API endpoint command. The JSON for searching must be in the following form:
{
resource_id: resource_id # resource id that the data is going to be stored under.
records: [] # a list of dictionaries of the data, eg: [{"dob": "2005", "some_stuff": ['a', b']}, ..]
method: # the method to use to put the data into the datastore
# possible options: upsert (default), insert, update
}- upsert
Update if record with same key already exists, otherwise insert. Requires unique key.
- insert
Insert only. This method is faster that upsert because checks are omitted. Does not require a unique key.
- update
Update only. Exception will occur if the key that should be updated does not exist. Requires unique key.
The datastore_search API endpoint allows a user to search data at a resource. The JSON for searching must be in the following form:
{
resource_id: # the resource id to be searched against
filters : # dictionary of matching conditions to select e.g {'key1': 'a. 'key2': 'b'}
# this will be equivalent to "select * from table where key1 = 'a' and key2 = 'b' "
q: # full text query
plain: # treat as plain text query (default: true)
language: # language of the full text query (default: english)
limit: # limit the amount of rows to size (default: 100)
offset: # offset the amount of rows
fields: # list of fields return in that order, defaults (empty or not present) to all fields in fields order.
sort: # ordered list of field names as, eg: "fieldname1, fieldname2 desc"
}The datastore_search_sql API endpoint allows a user to search data at a resource or connect multiple resources with join expressions. The underlying SQL engine is the PostgreSQL engine. The JSON for searching must be in the following form:
{
sql: # a single sql select statement
}Note
HTSQL is not in the core datastore and has to be installed as an extension. The extension is available on https://github.com/okfn/ckanext-htsql.
The datastore_search_htsql API endpoint allows a user to search data at a resource using the HTSQL query expression language. The JSON for searching must be in the following form:
{
htsql: # a htsql query statement.
}Fields define the column names and the type of the data in a column. They are defined as an array of fields. One field is defined as follows:
{
"id": # a string which defines the column name
"type": # the data type for the column
}Field types are optional and will be guessed by the provided data. However, setting the types ensures that future inserts to not fail because of wrong types. See valid-types for details on which types are valid.
Example:
[
{
"id": "foo",
"type": "int4"
},
{
"id": "bar"
# type is optional
}
]Records are defined as an array of records. One record is the data to be inserted in a table and is defined as follows:
{
"<id>": # data to be set
# .. more data
}Example:
[
{
"foo": 100,
"bar": "I'm a text."
},
{
"foo": 42
}
]The datastore supports all types supported by PostgreSQL as well as a few additions. A list of the PostgreSQL types can be found in the documentation. Below you can find a list of the most common data types. The json type has been added as a storage for nested data.
- text
Arbitrary text data, e.g.
I'm a text.- date
Date without time, e.g
2012-5-25- time
Time without date, e.g
12:42- timestamp
Date and time, e.g
2012-10-01T02:43Z.- int4
Integer numbers, e.g
42,7.- float8
Floats, e.g.
1.61803.- bool
Boolen values, e.g.
true,0
Resources in the datastore can have multiple aliases that are easier to remember than the resource id. Aliases can be created and edited with the datastore_create API endpoint. All aliases can be found in a special view called _table_metadata.
The datastore supports querying with the datastore_search and datastore_search_sql API endpoint. They are similar but support different features. The following list gives an overview on the different methods.
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| ============================== | ======================= | =========================== | ============================= |
| Status | Stable | Stable | Available as extension |
| Ease of use | Easy | Complex | Medium |
| Flexibility | Low | High | Medium |
| Query language | Custom (JSON) | SQL | HTSQL |
| Connect multiple resources | No | Yes | Not yet |
| Use aliases | Yes | Yes | Yes |