Databricks-Certified-Professional-Data-Engineer Exam Dumps : Databricks Certified Data Engineer Professional Exam

It is retained until you export or delete job run logs

It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3

t is retained for 60 days, during which you can export notebook run results to HTML

It is retained for 60 days, after which logs are archived

It is retained for 90 days or until the run-id is re-used through custom run configuration

Structured Streaming leverages the parallel processing of GPUs to achieve highly parallel data throughput.

Structured Streaming is implemented as a messaging bus and is derived from Apache Kafka.

Structured Streaming uses specialized hardware and I/O streams to achieve sub-second latency for data transfer.

Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.

Structured Streaming relies on a distributed network of nodes that hold incremental state values for cached stages.

%sh triggers a cluster restart to collect and install Git. Most of the latency is related to cluster startup time.

Instead of cloning, the code should use %sh pip install so that the Python code can get executed in parallel across all nodes in a cluster.

%sh does not distribute file moving operations; the final line of code should be updated to use %fs instead.

Python will always execute slower than Scala on Databricks. The run.py script should be refactored to Scala.

%sh executes shell code on the driver node. The code does not take advantage of the worker nodes or Databricks optimized Spark.