You plan to create an operational system that will store data in an Azure Cosmos DB Core (SQL) API account. You need to configure the account to meet the following requirements: - Support Spark…

Enabling Azure Synapse Link for the Cosmos DB account is fundamental as it allows near real-time analytics over operational data without impacting transactional workloads, supporting Spark queries and the pay-per-query model.

Setting the analyticalTTL property to six months on the container ensures that data is retained in the analytical store for the required duration, allowing analysis of the last six months of data.

Creating an Azure Databricks notebook allows you to write and execute Spark queries against the analytical store connected via Azure Synapse Link, meeting the "Support Spark queries" requirement by providing the necessary compute environment.

Creating an Azure Synapse linked service is a connection step, but it doesn't directly provide the Spark compute environment for running queries; an option like Azure Databricks (C) or a Synapse Spark pool is needed for execution.

Setting the time to live (transactional TTL) to six months would delete documents from the operational store, which is not the requirement; the requirement is to analyze data from the last six months, implying its presence in the analytical store, not its deletion from the transactional store.

Creating an Azure Synapse pipeline orchestrates data movement and transformation, but it doesn't directly enable the analytical store feature or provide the Spark compute environment required for querying.