- Recipes
- Google BigQuery to Amazon S3 NDJSON file
Connect Google BigQuery and Amazon S3 NDJSON file in our serverless environment
Use this template to Read rows from Google BigQuery table using them to create NDJSON file entries in Amazon S3 Bucket.
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Read rows from Google BigQuery table
Used integrations:
- JavaScript
- Python
class GoogleBigquerySourceSelect {
async init() {
// TODO: Create your google-bigquery credential
// More info at https://yepcode.io/docs/integrations/google-bigquery/#credential-configuration
this.googleBigQuery = yepcode.integration.googleBigQuery(
"your-google-bigquery-credential-name"
);
}
async fetch(publish, done) {
// TODO: Customize your query
const query = `SELECT *
FROM \`your_db.your_schema.your_table_name\`
LIMIT 10`;
// for all options, see https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query
const options = {
query: query,
// Location must match that of the dataset(s) referenced in the query.
location: "US",
};
// run the query as a job
const [job] = await this.googleBigQuery.createQueryJob(options);
console.log(`Job ${job.id} started.`);
// wait for the query to finish
const [rows] = await job.getQueryResults();
for (const row of rows) {
await publish(row);
}
done();
}
async close() {}
}
class GoogleBigquerySourceSelect:
def setup(self):
# TODO: Create your BigQuery credential:
# More info at https://yepcode.io/docs/integrations/google-bigquery/#credential-configuration
self.big_query_client = yepcode.integration.googleBigQuery(
"your-bigquery-credential-name"
)
def generator(self):
# TODO: Customize dataset and table ids and query content
dataset_id = "dataset_id"
table_id = "table_id"
query = (
f"SELECT * FROM `{self.big_query_client.project}.{dataset_id}.{table_id}`"
)
query_job = self.big_query_client.query(query)
rows = query_job.result()
for row in rows:
yield row
def close(self):
pass
Do you need help solving this integration with YepCode?
Let's talkCreate NDJSON file entries in Amazon S3 Bucket
Used integrations:
- JavaScript
- Python
class AwsS3TargetUploadNdjson {
async init() {
// TODO: Create your aws-s3 credential
// More info at https://yepcode.io/docs/integrations/aws-s3/#credential-configuration
const awsS3 = yepcode.integration.awsS3("your-aws-s3-credential-name");
// Transforms the items into a ndjson format
this.stringifier = ndjson.stringify();
const targetStream = new PassThrough();
this.stringifier.pipe(targetStream);
// TODO: customize the Upload content
// More info at: https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/interfaces/_aws_sdk_lib_storage.options-1.html
const upload = new Upload({
client: awsS3,
params: {
Bucket: "your-bucket-name",
Key: "your-file-name.ndjson",
Body: targetStream,
},
});
upload.on("httpUploadProgress", (progress) => {
console.log(`Upload progress`, progress);
});
this.uploadPromise = upload.done();
}
async consume(item) {
this.stringifier.write(item);
}
async close() {
try {
this.stringifier.end();
} catch (error) {
console.error(`Error ending stringifier`, error);
}
try {
await this.uploadPromise;
} catch (error) {
console.error(`Error ending upload`, error);
}
}
}
import ndjson
import io
class AccumulatingStream:
def __init__(self):
self.data = io.BytesIO()
def write(self, item):
self.data.write(item.encode("utf-8"))
def get_stream(self):
self.data.seek(0)
return self.data
class AwsS3TargetUploadNdjson:
def setup(self):
# TODO: Create your S3 credential:
# More info at https://yepcode.io/docs/integrations/aws-s3/#credential-configuration
self.aws_s3_client = yepcode.integration.awsS3("your-s3-credential-name")
self.acc_stream = AccumulatingStream()
self.stringifier = ndjson.writer(self.acc_stream, ensure_ascii=False)
def consume(self, generator, done):
for item in generator:
self.stringifier.writerow(item)
done()
def close(self):
# TODO: customize the bucket name and object key
try:
self.aws_s3_client.upload_fileobj(
self.acc_stream.get_stream(),
"bucket-name",
"path/to/object.ndjson",
)
except Exception as error:
print(f"Error uploading object: {error}")
FAQs
YepCode is a SaaS platform that enables the creation, execution and monitoring of integrations and automations using source code in a serverless environment.
We like to call it the Zapier for developers, since we bring all the agility and benefits of NoCode tools (avoid server provisioning, environment configuration, deployments,...), but with all the power of being able to use a programming language like JavaScript or Python.
These recipes are an excellent starting point for creating your own YepCode processes and solving complex integration and automation problems.
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