bigquery
v0.0.6
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This is a simple sdk for using google bigquery. Still working... if any problem, please let me know. Want to know what is BigQuery? Look my slide: http://www.slideshare.net/peihsinsu/google-bigquery-introduction
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bigquery
This is a simple sdk for using google bigquery. Still working... if any problem, please let me know. Want to know what is BigQuery? Look my slide: http://www.slideshare.net/peihsinsu/google-bigquery-introduction
Installation
npm install bigquery
Apply service account
Follow the doc: http://gappsnews.blogspot.tw/2013/10/connect-cloud-platform-bigquery-using.html
Convert p12 key (If use old version service account...)
From admin console, create a service account, save the client_secrets.json and it's key ex: Translate p12 to pem
openssl pkcs12 -in privatekey.p12 -out privatekey.pem -nocerts
openssl rsa -in privatekey.pem -out key.pem
or
openssl pkcs12 -in privatekey.p12 -nodes -nocerts > key.pem
Initial using Service Account json_file
If you are create the service account after 2015Q2, you will find the service account provide a json file formate download. The json file is like:
{
"private_key_id": "e7************************************e8",
"private_key": "-----BEGIN PRIVATE KEY-----\nMIIC***....skip...****AFW1Y\n-----END PRIVATE KEY-----\n",
"client_email": "86*********8-if***************************[email protected]",
"client_id": "86*********8-if***************************pq2.apps.googleusercontent.com",
"type": "service_account"
}
The file is already include the secret file and the account information. We support to use the file for easy auth.
var bq = require('bigquery')
bq.init({
json_file: '/path/to/your-service-account-json-file.json'
});
Initial using client_email directly
About 2015Q1 end, google start to deprecate the client_secret file download. You can change the init method like this:
bq.init({
client_email: '[email protected]',
key_pem: '/path-to-key.pem'
});
Initial using old client_secret.json (will deprecated)
Load bigquery lib, specify your project id then setup the service account and the client_secret.json file path, pem key file path for auth use.
var bq = require('bigquery')
, fs = require('fs')
, prjId = 'your-bigquery-project-id'; //you need to modify this
bq.init({
client_secret: '/path-to-client_secret.json',
key_pem: '/path-to-key.pem'
});
Do Query
Query the dataset that you have. The sample bellow is to query the public dataset of wikipedia.
bq.job.query(prjId, 'select count(*) from publicdata:samples.wikipedia', function(e,r,d){
if(e) console.log(e);
console.log(JSON.stringify(d));
});
Get Query Results
Retrieve results from a previously run query. Larger queries will timeout and respond with no data before the results are collected. Use this to retrieve the results. Below is an example of querying and waiting for results.
bq.job.query(prjId, 'select count(*) from publicdata:samples.wikipedia', function(e,r,d){
if(e) console.log(e);
if(d.jobIsComplete){
console.log(JSON.stringify(d));
} else {
bq.job.getQueryResults(prjId, d.jobReference.jobId, function(e,r,d){
console.log(JSON.stringify(d));
}
}
});
Load data
Before load data, you must create your dataset and table first. After that, you can use the following code to load data. (In this case test is the dataset id, testtb1 is the table name.)
var data = [
{
"insertId": "201403221228", //option
"json": {
"name": "simon",
"sex": "M",
"age": 35
}
}
];
bq.job.load(prjId, 'test', 'testtb1', data, function(e,r,d){
if(e) console.log(e);
console.log(JSON.stringify(d));
})
PS: The insertId use for prevent the duplicate insert of data.
Create Dataset & Table
Create dataset and table, the schema please ref: https://developers.google.com/bigquery/preparing-data-for-bigquery
bq.dataset.create(prjId, 'dataset_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
var schema = {
"fields": [
{
"name": "field1",
"type": "string",
"description": "test"
},
{
"name": "field2",
"type": "integer",
"description": "test for int"
}
]
};
bq.table.create(prjId, 'dataset_name', 'table_name', schema, function(e,r,d){
if(e) console.log(e);
console.log(d);
});
Get Table
bq.table.get(prjId, 'test123', 'table_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
Delete Table
bq.table.delete(prjId, 'dataset_name', 'table_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
Get Dataset
bq.dataset.get(prjId, 'dataset_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
Delete Dataset
bq.dataset.delete(prjId, 'dataset_name', 'table_name2', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
Other request timeout parameters
If you want to add timeout parameter to restrict to your bigquery api request time. You can add timeout parameter to the init() like:
bq.init({
client_secret: __dirname + '/client_secret.json',
key_pem: __dirname + '/key.pem',
timeout:1000
});