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Choose the best response for each of the questions.
What is the role of Spark Structured Streaming in setting up real-time data sources for incremental processing with Azure Databricks?
It's used to process real-time data streams using the same DataFrame and Dataset APIs used for batch processing.
It's used to store the processed data in Delta tables.
It's used to configure the data sources that provide the real-time data streams.
What is the purpose of using Z-Order Clustering in optimizing Delta Lake for incremental processing in Azure Databricks?
To enable data skipping and indexing
To manage metadata efficiently
To optimize the storage layout of data files, enhancing query performance
What is the purpose of watermarking in handling late data and out-of-order events in incremental processing in Azure Databricks?
Watermarking is used to duplicate records using unique identifiers or a combination of event attributes.
Watermarking sets a threshold for how long the system should wait for late data. Events arriving after the watermark are considered late and can be discarded or considered separately, reducing memory usage and ensuring timely processing.
Watermarking is used to adjust processing logic based on the observed latency patterns, dynamically modifying how late data is handled to balance accuracy and performance.
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