1.8.0 kyuubi.engine.chat. gpt.model gpt-3.5- turbo ID of the model used in ChatGPT. Available models refer to OpenAI's Model overview. strin g 1.8.0 Key Default Meaning Type Since kyuubi.engine.chat resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely

1.8.0 kyuubi.engine.chat. gpt.model gpt-3.5- turbo ID of the model used in ChatGPT. Available models refer to OpenAI's Model overview. strin g 1.8.0 Key Default Meaning Type Since kyuubi.engine.chat resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely

1.8.0 kyuubi.engine.chat. gpt.model gpt-3.5- turbo ID of the model used in ChatGPT. Available models refer to OpenAI's Model overview. strin g 1.8.0 Key Default Meaning Type Since kyuubi.engine.chat resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient 3.7. Extensions 137 Kyuubi, Release 1.7.3 Supported table format Supported column data type

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient 134 Chapter 3. What’s Next Kyuubi, Release 1.7.1 Supported table format Supported column data

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient 3.7. Extensions 137 Kyuubi, Release 1.7.3 Supported table format Supported column data type

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient 3.7. Extensions 137 Kyuubi, Release 1.7.2 Supported table format Supported column data type

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient 3.7. Extensions 137 Kyuubi, Release 1.7.2 Supported table format Supported column data type

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient Supported table format Supported column data type How to use This feature is inside Kyuubi extension

resources more efficiently. On the one hand, we need to rely on the resource manager’s capabilities for efficient resource allocation, resource isolation, and sharing. On the other hand, we need to enable Spark’s Handle Skew Joins Without AQE, the data skewness is very likely to occur for map-reduce computing models in the shuffle phase. Data skewness can cause Spark jobs to have one or more tailing tasks, severely data e.g. minimum and maximum values, the good data clustering let the pushed down filter more efficient 3.8. Extensions 139 Kyuubi, Release 1.8.0 Supported table format Supported column data type