on one platform, using one copy of data, with one SQL interface. Kyuubi provides the following features: Multi-tenancy Kyuubi supports the end-to-end multi-tenancy, and this is why we want to create should also increase skewedPartitionThresholdInBytes if you tend to enable the feature. Hidden Features DemoteBroadcastHashJoin Internally, Spark has an optimization rule that detects a join child with This optimization rule detects and converts a Join to an empty LocalRelation. Disabling the Hidden Features We can exclude some of the AQE additional rules if performance regression or bug occurs. For example

on one platform, using one copy of data, with one SQL interface. Kyuubi provides the following features: Multi-tenancy Kyuubi supports the end-to-end multi-tenancy, and this is why we want to create should also increase skewedPartitionThresholdInBytes if you tend to enable the feature. Hidden Features DemoteBroadcastHashJoin Internally, Spark has an optimization rule that detects a join child with This optimization rule detects and converts a Join to an empty LocalRelation. Disabling the Hidden Features We can exclude some of the AQE additional rules if performance regression or bug occurs. For example

CSI 自动迁移排空，然后按顺序重启集群中的所有节点。这可能需要一些时间。 流程 流程 启用功能门（请参阅 Nodes → working with cluster → Enabling features using feature gates ）。 重要 重要 在使用功能门开启技术预览功能后，无法关闭它们。因此，集群升级会被阻止。 以下配置示例启用 CSI 自动迁移到 CSI 驱动程序（AWS TechPreviewNoUpgrade 功能集启用功能门。 流程 流程 1. 通过 TechPreviewNoUpgrade 功能集启用功能门（请参阅 Nodes → Enabling features using feature gates）。 重要 重要 在使用功能门（feature gate）启用技术预览功能后，无法关闭这些技术预览功 能，并会防止集群升级。 2. 验证集群操作器存储： VERSION AVAILABLE PROGRESSING DEGRADED SINCE storage 4.8.0-0.nightly-2021-04-30-201824 True False False 4h26m OpenShift Container Platform 4.8 存

tensorflow-gpu —Current release with GPU support (Ubuntu and Windows) tf-nightly —Nightly build for CPU-only (unstable) tf-nightly-gpu —Nightly build with GPU support (unstable, Ubuntu and Windows) “Hello TensorFlow” tensorflow/tensorflow:nightly-jupyter 4. Start a TensorFlow Docker container $ docker run -it -p 8888:8888 -v $(notebook-examples-path):/tf/notebooks tensorflow/tensorflow:nightly-jupyter “Hello TensorFlow”

lamabda, runpod, fluidstack, paperspace, # cudo, ibm, scp, vsphere, kubernetes pip install "skypilot-nightly[aws,gcp]" 随后，您需要用如下命令确认是否能使用云： sky check For more information, check the official document and aws:/root/.aws:rw" \ -v "$HOME/.config/gcloud:/root/.config/gcloud:rw" \ berkeleyskypilot/skypilot-nightly docker exec -it sky /bin/bash 1.11.3 使用 SkyPilot 运行 Qwen1.5-72B-Chat 1. 您可以使用 serve-72b.yaml 中的可用的

3.0.0, ...) • API-breaking changes will be made only in major releases (except for experimental features) See Version Policy for more. {{ header }} 1.2 Enhancements 1.2.1 Using Numba in rolling.apply | A | B | |:---|----:|----:| | a | 1 | 1 | | a | 2 | 2 | | b | 3 | 3 | 1.3 Experimental new features 1.3.1 Experimental NA scalar to denote missing values A new pd.NA value (singleton) is introduced string dtype. In [12]: s.str.upper() Out[12]: 0 ABC (continues on next page) 1.3. Experimental new features 5 pandas: powerful Python data analysis toolkit, Release 1.0.0 (continued from previous page)

reindex() is the fundamental data alignment method in pandas. It is used to implement nearly all other features relying on label-alignment functionality. To reindex means to conform the data to match a given freedom and flexibility in interactive data analysis and research. The integrated data alignment features of the pandas data structures set pandas apart from the majority of related tools for working with pandas operations are shown below. In addition to these functions pandas supports other Time Series features not available in Base SAS (such as resampling and custom offsets) - see the timeseries documentation

Routines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 718 2.16.10 Other useful features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 719 2.16.11 Examples pandas operations are shown below. In addition to these functions pandas supports other Time Series features not available in Base SAS (such as resampling and custom offsets) - see the timeseries documentation pandas operations are shown below. In addition to these functions, pandas supports other Time Series features not available in Stata (such as time zone handling and custom offsets) – see the timeseries documentation

Routines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 718 2.16.10 Other useful features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 719 2.16.11 Examples pandas operations are shown below. In addition to these functions pandas supports other Time Series features not available in Base SAS (such as resampling and custom offsets) - see the timeseries documentation pandas operations are shown below. In addition to these functions, pandas supports other Time Series features not available in Stata (such as time zone handling and custom offsets) – see the timeseries documentation

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 703 iii 2.13.9 Other useful features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 705 2.13.10 Examples reindex() is the fundamental data alignment method in pandas. It is used to implement nearly all other features relying on label-alignment functionality. To reindex means to conform the data to match a given freedom and flexibility in interactive data analysis and research. The integrated data alignment features of the pandas data structures set pandas apart from the majority of related tools for working with