CouchImport
Introduction
When populating CouchDB databases, often the source of the data is initially a CSV or TSV file. couchimport is designed to assist you with importing flat data into CouchDB efficiently.
It can be used either as command-line utilities couchimport
and couchexport
or the underlying functions can be used programmatically:
- simply pipe the data file to couchimport on the command line.
- handles tab or comma-separated data.
- uses Node.js's streams for memory efficiency.
- plug in a custom function to add your own changes before the data is written.
- writes the data in bulk for speed.
- can also read huge JSON files using a streaming JSON parser.
- allows multiple HTTP writes to happen at once using the
--parallelism
option.
Installation
Requirements
- node.js = npm
sudo npm install -g couchimport
Configuration
couchimport's configuration parameters can be stored in environment variables or supplied as command line arguments.
The location of CouchDB
Simply set the COUCH_URL
environment variable e.g. for a hosted Cloudant database
export COUCH_URL="https://myusername:myPassw0rd@myhost.cloudant.com"
or a local CouchDB installation:
export COUCH_URL="http://localhost:5984"
IAM Authentication
Alternatively, if you are using IAM authentication with IBM Cloudant, then supply two environment variables:
COUCH_URL
- the URL of your Cloudant host e.g.https://myhost.cloudant.com
(note absence of username and password in URL).IAM_API_KEY
- the IAM API KEY e.g.ABC123515-151215
.
The name of the database - default "test"
Define the name of the CouchDB database to write to by setting the COUCH_DATABASE
environment variable e.g.
export COUCH_DATABASE="mydatabase"
Transformation function - default nothing
Define the path of a file containing a transformation function e.g.
export COUCH_TRANSFORM="/home/myuser/transform.js"
The file should:
- be a JavaScript file
- export one function that takes a single doc and returns a single object or an array of objects if you need to split a row into multiple docs.
(see examples directory).
Delimiter - default "\t"
The define the column delimiter in the input data e.g.
export COUCH_DELIMITER=","
Running
Simply pipe the text data into "couchimport":
cat ~/test.tsv | couchimport
This example downloads public crime data, unzips and imports it:
curl 'http://data.octo.dc.gov/feeds/crime_incidents/archive/crime_incidents_2013_CSV.zip' > crime.zip
unzip crime.zip
export COUCH_DATABASE="crime_2013"
export COUCH_DELIMITER=","
ccurl -X PUT /crime_2013
cat crime_incidents_2013_CSV.csv | couchimport
In the above example we use (ccurl)[https://github.com/glynnbird/ccurl], a command-line utility that uses the same environment variables as couchimport.
Output
The following output is visible on the console when "couchimport" runs:
couchimport
-----------
url : "https://****:****@myhost.cloudant.com"
database : "test"
delimiter : "\t"
buffer : 500
parallelism : 1
type : "text"
-----------
couchimport Written ok:500 - failed: 0 - (500) +0ms
couchimport { documents: 500, failed: 0, total: 500, totalfailed: 0 } +0ms
couchimport Written ok:499 - failed: 0 - (999) +368ms
couchimport { documents: 499, failed: 0, total: 999, totalfailed: 0 } +368ms
couchimport writecomplete { total: 999, totalfailed: 0 } +0ms
couchimport Import complete +81ms
The configuration, whether default or overriden by environment variables or command line arguments, is shown. This is followed by a line of output for each block of 500 documents written, plus a cumulative total.
Preview mode
If you want to see a preview of the JSON that would be created from your csv/tsv files then add --preview true
to your command-line:
> cat text.txt | couchimport --preview true
Detected a TAB column delimiter
{ product_id: '1',
brand: 'Gibson',
type: 'Electric',
range: 'ES 330',
sold: 'FALSE' }
As well as showing a JSON preview, preview mode also attempts to detect the column delimiter character for you.
Importing large JSON documents
If your source document is a GeoJSON text file, couchimport
can be used. Let's say your JSON looks like this:
{ "features": [ { "a":1}, {"a":2}] }
and we need to import each feature object into CouchDB as separate documents, then this can be imported using the type="json"
argument and specifying the JSON path using the jsonpath
argument:
cat myfile.json | couchimport --database mydb --type json --jsonpath "features.*"
Importing JSON Lines file
If your source document is a JSON Lines text file, couchimport
can be used. Let's say your JSON Lines looks like this:
{"a":1}
{"a":2}
{"a":3}
{"a":4}
{"a":5}
{"a":6}
{"a":7}
{"a":8}
{"a":9}
and we need to import each line as a JSON object into CouchDB as separate documents, then this can be imported using the type="jsonl"
argument:
cat myfile.json | couchimport --database mydb --type jsonl
Importing a stream of JSONs
If your source data is a lot of JSON objects meshed or appended together, couchimport
can be used. Let's say your file:
{"a":1}{"a":2} {"a":3}{"a":4}
{"a":5} {"a":6}
{"a":7}{"a":8}
{"a":9}
and we need to import each JSON objet to CouchDB as separate documents, then this can be imported using the type="jsonl"
argument:
cat myfile.json.blob | couchimport --database mydb --type jsonl
Overwriting existing data
If you are importing data into a CouchDB database that already contains data, and you are supplying a document _id
in your source data, then and values of _id
will fail to write because CouchDB will report a 409 Document Conflict
. If you want your supplied data to supercede existing data then supply --overwrite true
/-o true
as a command-line option. This will instruct couchimport
to fetch the existing documents' current _rev
values and inject them into the imported data stream.
Note: Using overwrite mode is slower because an additional API call is required per batch of data imported. USe caution when importing data into a data set that is being changed by another actor at the same time.
Environment variables
- COUCH_URL - the url of the CouchDB instance (required, or to be supplied on the command line)
- COUCH_DATABASE - the database to deal with (required, or to be supplied on the command line)
- COUCH_DELIMITER - the delimiter to use (default '\t', not required)
- COUCH_TRANSFORM - the path of a transformation function (not required)
- COUCHIMPORT_META - a json object which will be passed to the transform function (not required)
- COUCH_BUFFER_SIZE - the number of records written to CouchDB per bulk write (defaults to 500, not required)
- COUCH_FILETYPE - the type of file being imported, either "text", "json" or "jsonl" (defaults to "text", not required)
- COUCH_JSON_PATH - the path into the incoming JSON document (only required for COUCH_FILETYPE=json imports)
- COUCH_PREVIEW - run in preview mode
- COUCH_IGNORE_FIELDS - a comma-separated list of field names to ignore on import or export e.g. price,url,image
- COUCH_OVERWRITE - overwrite existing document revisions with supplied data
Command-line parameters
You can also configure couchimport
and couchexport
using command-line parameters:
--help
- show help--version
- simply prints the version and exits--url
/-u
- the url of the CouchDB instance (required, or to be supplied in the environment)--database
/--db
/-d
- the database to deal with (required, or to be supplied in the environment)--delimiter
- the delimiter to use (default '\t', not required)--transform
- the path of a transformation function (not required)--meta
/-m
- a json object which will be passed to the transform function (not required)--buffer
/-b
- the number of records written to CouchDB per bulk write (defaults to 500, not required)--type
/-t
- the type of file being imported, either "text", "json" or "jsonl" (defaults to "text", not required)--jsonpath
/-j
- the path into the incoming JSON document (only required for type=json imports)--preview
/-p
- if 'true', runs in preview mode (default false)--ignorefields
/-i
- a comma-separated list of fields to ignore input or output (default none)--parallelism
- the number of HTTP request to have in flight at any one time (default 1)--overwrite
/-o
- overwrite existing document revisions with supplied data (default: false)
e.g.
cat test.csv | couchimport --database bob --delimiter ","
couchexport
If you have structured data in a CouchDB or Cloudant that has fixed keys and values e.g.
{
"_id": "badger",
"_rev": "5-a9283409e3253a0f3e07713f42cd4d40",
"wiki_page": "http://en.wikipedia.org/wiki/Badger",
"min_weight": 7,
"max_weight": 30,
"min_length": 0.6,
"max_length": 0.9,
"latin_name": "Meles meles",
"class": "mammal",
"diet": "omnivore",
"a": true
}
then it can be exported to a CSV like so (note how we set the delimiter):
couchexport --url http://localhost:5984 --database animaldb --delimiter "," > test.csv
or to a TSV like so (we don't need to specify the delimiter since tab \t
is the default):
couchexport --url http://localhost:5984 --database animaldb > test.tsv
or to a stream of JSON:
couchexport --url http://localhost:5984 --database animaldb --type jsonl
N.B.
- design documents are ignored
- the first non-design document is used to define the headings
- if subsequent documents have different keys, then unexpected things may happen
- COUCH_DELIMITER or --delimiter can be used to provide a custom column delimiter (not required when tab-delimited)
- if your document values contain carriage returns or the column delimiter, then this may not be the tool for you
- you may supply a JavaScript
--transform
function to modify the data on its way out
Using programmatically
In your project, add couchimport
into the dependencies of your package.json or run npm install couchimport
. In your code, require
the library with
var couchimport = require('couchimport');
and your options are set in an object whose keys are the same as the COUCH_* environment variables:
e.g.
var opts = { delimiter: ",", url: "http://localhost:5984", database: "mydb" };
To import data from a readable stream (rs):
var rs = process.stdin;
couchimport.importStream(rs, opts, function(err,data) {
console.log("done");
});
To import data from a named file:
couchimport.importFile("input.txt", opts, function(err,data) {
console.log("done",err,data);
});
To export data to a writable stream (ws):
var ws = process.stdout;
couchimport.exportStream(ws, opts, function(err, data) {
console.log("done",err,data);
});
To export data to a named file:
couchimport.exportFile("output.txt", opts, function(err, data) {
console.log("done",err,data);
});
To preview a file:
couchimport.previewCSVFile('./hp.csv', opts, function(err, data, delimiter) {
console.log("done", err, data, delimiter);
});
To preview a CSV/TSV on a URL:
couchimport.previewURL('https://myhosting.com/hp.csv', opts, function(err, data) {
console.log("done", err, data, delimiter);
});
Monitoring an import
Both importStream
and importFile
return an EventEmitter which emits
written
event on a successful writewriteerror
event when a complete write operation failswritecomplete
event after the last write has finishedwritefail
event when an individual line in the CSV fails to be saved as a doc
e.g.
couchimport.importFile("input.txt", opts, function(err,data) {
console.log("done",err,data);
}).on("written", function(data) {
// data = { documents: 500, failed:6, total: 63000, totalfailed: 42}
});
The emitted data is an object containing:
- documents - the number of documents written in the last batch
- total - the total number of documents written so far
- failed - the number of documents failed to write in the last batch
- totalfailed - the number of documents that failed to write in total
Parallelism
Using the COUCH_PARALLELISM
environment variable or the --parallelism
command-line option, couchimport can be configured to write data in multiple parallel operations. If you have the networkbandwidth, this can significantly speed up large data imports e.g.
cat bigdata.csv | couchimport --database mydb --parallelism 10 --delimiter ","