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bigquery
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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
npm install bigquery
Follow the doc: http://gappsnews.blogspot.tw/2013/10/connect-cloud-platform-bigquery-using.html
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
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***************************pq2@developer.gserviceaccount.com",
"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'
});
About 2015Q1 end, google start to deprecate the client_secret file download. You can change the init method like this:
bq.init({
client_email: 'your-client-email@developer.gserviceaccount.com',
key_pem: '/path-to-key.pem'
});
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'
});
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));
});
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));
}
}
});
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 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);
});
bq.table.get(prjId, 'test123', 'table_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
bq.table.delete(prjId, 'dataset_name', 'table_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
bq.dataset.get(prjId, 'dataset_name', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
bq.dataset.delete(prjId, 'dataset_name', 'table_name2', function(e,r,d){
if(e) console.log(e);
console.log(d);
});
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
});
FAQs
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
The npm package bigquery receives a total of 70 weekly downloads. As such, bigquery popularity was classified as not popular.
We found that bigquery demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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