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Премиум
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    01. Introduction
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    02. Certification Exam Overview
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    03. Signing up for Databricks Community Edition
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    04. Loading Data Into Databricks
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    05. Overview of the Spark Cluster Architecture and its Components
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    06. Getting to Know the Spark Driver
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    07. Getting to Know Executors
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    08. Discovering Execution Modes
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    09. Overview
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    10. Internal Types, DataFrames, Datasets, RDDs, and the Spark SQL API
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    11. Hands-on Session_ Exploring Data APIs on Databricks Community Edition
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    12. Intro to Labs
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    13. Intro & Creating DataFrames
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    14. Exercise_ Creating a DataFrame
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    15. Exercise_ Creating a DataFrame - Solution
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    16. Working with Schemas
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    17. Exercise_ Building a Simple Schema
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    18. Exercise_ Building a Simple Schema - Solution
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    19. Exercise_ Building a Complex Schema
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    20. Exercise_ Building a Complex Schema - Solution
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    21. Type Conversion of DataFrame Columns
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    22. Exercise_ Changing the Type of a Column
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    23. Exercise_ Changing the Type of a Column - Solution
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    24. Overview
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    25. Shuffles
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    26. Data Skew
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    27. Spark Configurations for Partitions
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    28. Hands-on Session_ The Power of Partitions
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    29. Storage Layout
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    30. Caching and Storage Levels
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    31. Memory in Action
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    32. Hands-on Session_ Executor Memory Management - Part 1
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    33. Hands-on Session_ Executor Memory Management - Part 2
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    34. Intro & How to Get Help in PySpark
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    35. Partitioning Recap
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    36. Exercise_ Repartitioning
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    37. Exercise_ Repartitioning - Solution
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    38. Caching Recap
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    39. Exercise_ Caching
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    40. Exercise_ Caching - Solution
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    41. Overview
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    42. Hands-On Session_ Actions vs. Transformations
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    43. Intro & Reading Data
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    44. Exercise_ Reading Parquet Files
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    45. Exercise_ Reading Parquet Files - Solution
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    46. Reading from CSV Files
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    47. Exercise_ Reading CSV Files
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    48. Exercise_ Reading CSV Files - Solution
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    49. Reading from JSON Files
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    50. Writing Data
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    51. Exercise_ Writing to Parquet Files
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    52. Exercise_ Writing to Parquet Files - Solution
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    53. Writing to CSV Files
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    54. Exercise_ Writing to CSV Files
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    55. Exercise_ Writing to CSV Files - Solution
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    56. Writing to JSON Files
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    57. Using PySpark with SQL
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    58. Exercise_ SQL in PySpark
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    59. Exercise_ SQL in PySpark - Solution
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    60. Overview
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    61. Hands-on Session_ Discovering the Spark UI
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    62. Intro & Removing Data
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    63. Exercise_ Removing Data
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    64. Exercise_ Removing Data - Solution
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    65. Modifying Data
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    66. Exercise_ Modifying Data
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    67. Exercise_ Modifying Data - Solution
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    68. Analyzing Data
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    69. Exercise_ Analyzing Data
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    70. Exercise_ Analyzing Data - Solution
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    71. The Catalyst Optimizer
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    72. Adaptive Query Execution
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    73. Dynamic Partition Pruning
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    74. The DAG_ Achieving Fault Tolerance
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    75. Intro & Working With Dates and Times
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    76. Exercise_ Working With Dates and Times
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    77. Exercise_ Working With Dates and Times - Solution
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    78. Working With Strings
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    79. Exercise_ Working With Strings
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    80. Exercise_ Working With Strings - Solution
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    81. Working with Arrays
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    82. Exercise_ Working With Arrays
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    83. Exercise_ Working With Arrays - Solution
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    84. Accumulator and Broadcast Variables
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    85. Joins
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    86. Hands-on Session_ Cross-Cluster Communication
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    87. Intro & Grouping and Aggregating
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    88. Exercise_ Grouping and Aggregating
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    89. Exercise_ Grouping and Aggregating - Solution
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    90. Joining
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    91. Exercise_ Joining
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    92. Exercise_ Joining - Solution
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    93. User-Defined Functions (UDFs)
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    94. Exercise_ UDFs
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    95. Exercise_ UDFs - Solution
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    96. Signing up for the Exam
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    97. Last Minute Preparations
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    98. Introduction
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    99. Congratulations!