Javascript UDF’s are cool and using with NPM library is a whole new world to explore! Background One of the main reason to build ETL pipeline was to do data transformation on data before loading into the data warehouse. The only reason we were doing that because data warehouses were not capable to handle these data transformations due to several reasons such as performance and flexibility. In the era of modern data warehouses like Google BigQuery or SnowFlake , things have changed. These data warehouses can process terabyte and petabyte data within seconds and minutes. Considering this much improvement, now performing data transformation within a data warehouse make more sense. Hence to create common transformation logic via UDF (user-defined functions). In this blog, we will see how can we utilize the power of javascript UDF and NPM library to generate data in BigQuery. What is UDF? From Google Cloud Documentations: A user-defined function (UDF) lets you create a fun...
Ingesting API Data in Google BigQuery the Serverless way! API To Google BigQuery In the era of cloud computing, Serverless has become a buzzword that we keep hearing about, And eventually, we get convinced that serverless is the way to go for companies of all sizes because of various advantages. The basic advantages of the Serverless approach are : No Server Management Scalability Pay as you go In this article, we will also explore how we can use the Serverless approach to build our data Ingestion pipeline in Google Cloud. Serverless Offerings In GCP GCP offers plenty of Serverless Services in various areas such as mentioned below. Computing : Cloud Run, Cloud Function, App Engine Data warehouse : Google BigQuery Object Storage: Google Cloud Storage Workflow management : Cloud Workflow Scheduler: Cloud Scheduler Technically, the combination of the above tools is enough to build API data ingestion in GCP. We can build Two patterns to ingest API data in Google BigQu...