Upsert data

To upsert data means to update existing records or insert new records if they do not already exist. In the context of data engineering on Microsoft Azure, there are several techniques and tools available to achieve this. In this article, we will explore some of the popular methods for upserting data in Azure.

1. Upsert data using Azure Data Factory:

Azure Data Factory (ADF) is a cloud-based data integration service that allows you to build and orchestrate data-driven workflows. A common scenario is to use ADF to upsert data from one data store to another. Follow the steps below to perform an upsert operation using ADF:

– Create a pipeline in Azure Data Factory.

– Add a source dataset that references the data you want to upsert.

– Configure a lookup activity to check if the record already exists in the destination dataset.

– Use a conditional split activity to direct the data flow based on the condition.

– If the record exists, update it; if not, insert a new record.

– Finally, use a sink dataset to write the upserted data to the destination.

Here’s an example pipeline JSON code snippet that demonstrates this approach:

2. Upsert data using Azure Databricks and Delta Lake:

Azure Databricks is an Apache Spark-based analytics platform provided by Microsoft. Delta Lake is an open-source big data storage layer that provides ACID transactions and schema enforcement capabilities on top of Apache Spark. The combination of Azure Databricks and Delta Lake can be used to perform efficient upsert operations. Here’s an example of how you can achieve this:

– Create a Delta table in Azure Databricks:

%scala
import io.delta.tables._
import org.apache.spark.sql.functions._

val deltaTable = DeltaTable.forName(“tableName”)

// Upsert data using merge operation
deltaTable.as(“target”)
.merge(
sourceDataFrame.as(“source”),
“target.key = source.key”)
.whenMatched
.updateExpr(
Map(“column1” -> “source.value1”, “column2” -> “source.value2”))
.whenNotMatched
.insertExpr(
Map(“column1”, “value1”, “column2”, “value2”))
.execute()

3. Upsert data using Azure Cosmos DB:

Azure Cosmos DB is a globally distributed, multi-model database service. It provides a rich set of APIs and features for upserting data. When using Cosmos DB, you can perform an upsert operation by specifying the record’s primary key. If the record exists, it will be updated; if not, a new record will be inserted. Here’s an example using the SQL API:

– Connect to your Cosmos DB account using the appropriate SDK or tool.

– Execute an upsert query, specifying the primary key:

# Create a new document with upsert operation
{
“query”: “SELECT * FROM c WHERE c.id = @id”,
“parameters”: [
{
“name”: “@id”,
“value”: “recordId”
}
]
}

These are just a few examples of how you can upsert data in Microsoft Azure. Depending on your specific use case and requirements, there might be other tools and techniques that you can explore. The key is to leverage the capabilities provided by Azure services to efficiently handle upsert operations on your data.