Data & Schemas Knowledgebase

Real-time Data Ingestion from Kinesis to Incorta with PySpark

Learn how to ingest real time Kinesis data with PySpark.

Dynamic SQL Generation in PySpark

Use PySpark to generate SQL dynamically.

How to Ingest Data from AWS S3 to Incorta using Incorta PySpark MV

Learn how to and why you would choose to ingest data from S3 with an MV

Loading JSON data to Incorta using Materialized View - Part 1

SymptomsDiagnosisSolution1. Read Data into Spark2. Create JSON Schema3. Parse JSON and Create a Temporary Column4. Explode Nested JSON Array5. Save the Final DataFrame Download Symptoms JSON data are provided by the source system for sharing with ...

Incorta Integration with Sparkflows using Chidori

Integrate with Sparkflows using Chidori.

Save Your Work: Essential Tips for Incorta MV Notebook

Never lose your Incorta Notebook work.

Issue with converting a Pandas DataFrame to a Spark DataFrame

What to do if you receive the 'iteritems' error when trying to convert a Pandas DataFrame to Spark DataFrame.

Dynamic Forms in Materialized Views

Streamline your data investigation with the use of dynamic forms!

How to Check the Version of a Python Package

Sometimes you need to check the version of a Python package. Find out how!

Incorta Notebook Best Practices

We bet there is one thing in here you didn't know about working with notebooks in Incorta.

Use hash keys to compare two records in PySpark

Use hash keys to simplify duplicate record identification.

Informatica ETL migration to Incorta

Introduction When replacing your current Informatica ETL processes, there are many approaches you can take to seamlessly transition to Incorta. This document will cover some of the best practices around how to manage an Informatica migration to Inco...