Describe the process of integrating Hyperopt with Spark MLlib for hyperparameter tuning. What specific challenges might arise when attempting to parallelize the tuning process across a Spark cluster, and how can these be mitigated?

Simulated

Integrating Hyperopt with Spark MLlib is straightforward and involves no challenges.

11.5%

The main challenge is the incompatibility between Hyperopt and Spark MLlib, which cannot be resolved.

0.0%

Challenges include data serialization and synchronization issues across nodes, which can be mitigated by using efficient data handling techniques and careful configuration of the Spark cluster.

84.6%

Parallelizing the tuning process is not possible with Hyperopt and Spark MLlib.

3.8%

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Describe the process of integrating Hyperopt with Spark MLlib for hyperparameter tuning. What specific challenges might arise when attempting to parallelize the tuning process across a Spark cluster, and how can these be mitigated?