Machine Learning with Apache Spark

  1. Performance Tuning and Optimization
    1. Understanding Spark Performance
      1. Spark UI Analysis
        1. Accessing the Spark UI
          1. Jobs and Stages Monitoring
            1. Task-Level Metrics
              1. Storage Tab Analysis
                1. Environment Configuration
                  1. Executors Tab Insights
                  2. Performance Bottleneck Identification
                    1. CPU Bottlenecks
                      1. Memory Bottlenecks
                        1. I/O Bottlenecks
                          1. Network Bottlenecks
                          2. DAG Visualization
                            1. Stage Dependencies
                              1. Shuffle Operations
                                1. Optimization Opportunities
                              2. Data Management Optimization
                                1. Partitioning Strategies
                                  1. Hash Partitioning
                                    1. Range Partitioning
                                      1. Custom Partitioning
                                        1. Partition Pruning
                                        2. Shuffling Optimization
                                          1. Shuffle Impact on Performance
                                            1. Reducing Shuffle Operations
                                              1. Shuffle Partitions Tuning
                                                1. Broadcast Joins
                                                2. Data Skew Handling
                                                  1. Skew Detection
                                                    1. Salting Techniques
                                                      1. Custom Partitioners
                                                        1. Repartitioning Strategies
                                                        2. Caching and Persistence
                                                          1. When to Cache DataFrames
                                                            1. Storage Levels
                                                              1. MEMORY_ONLY
                                                                1. MEMORY_AND_DISK
                                                                  1. DISK_ONLY
                                                                    1. Serialized Storage
                                                                    2. Cache Management
                                                                      1. Unpersisting Data
                                                                    3. Spark Configuration Optimization
                                                                      1. Memory Management
                                                                        1. Executor Memory Configuration
                                                                          1. Driver Memory Configuration
                                                                            1. Memory Fractions
                                                                              1. Off-Heap Memory
                                                                              2. CPU and Parallelism
                                                                                1. Executor Cores
                                                                                  1. Dynamic Allocation
                                                                                    1. Parallelism Levels
                                                                                      1. Task Scheduling
                                                                                      2. Serialization Optimization
                                                                                        1. Kryo Serialization
                                                                                          1. Java Serialization
                                                                                            1. Custom Serializers
                                                                                            2. Garbage Collection Tuning
                                                                                              1. GC Algorithms
                                                                                                1. GC Parameters
                                                                                                  1. Memory Pressure Monitoring
                                                                                                  2. Network Optimization
                                                                                                    1. Network Protocols
                                                                                                      1. Compression Settings
                                                                                                        1. Bandwidth Utilization
                                                                                                      2. ML-Specific Optimizations
                                                                                                        1. Algorithm Selection
                                                                                                          1. Scalability Characteristics
                                                                                                            1. Computational Complexity
                                                                                                              1. Memory Requirements
                                                                                                              2. Feature Engineering Optimization
                                                                                                                1. Vectorization
                                                                                                                  1. Sparse vs Dense Representations
                                                                                                                    1. Feature Selection Impact
                                                                                                                    2. Model Training Optimization
                                                                                                                      1. Convergence Criteria
                                                                                                                        1. Early Stopping
                                                                                                                          1. Checkpointing
                                                                                                                          2. Large-Scale ML Best Practices
                                                                                                                            1. Resource Planning
                                                                                                                              1. Cluster Sizing
                                                                                                                                1. Cost Optimization
                                                                                                                                  1. Debugging Strategies
                                                                                                                                    1. Performance Monitoring
                                                                                                                                      1. Capacity Planning

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                                                                                                                                  9. Advanced Topics and Deployment

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                                                                                                                                  1. Introduction to Machine Learning with Apache Spark