{"id":50145,"date":"2023-04-14T16:27:12","date_gmt":"2023-03-16T06:54:00","guid":{"rendered":"https:\/\/www.silicloud.com\/zh\/blog\/%e5%88%a9%e7%94%a8cassandra%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e5%88%86%e6%9e%90%e7%9a%84%e6%96%b9%e6%b3%95-%e5%85%85%e5%88%86%e5%88%a9%e7%94%a8gpu%e5%92%8crapids\/"},"modified":"2024-04-29T23:29:44","modified_gmt":"2024-04-29T15:29:44","slug":"%e5%88%a9%e7%94%a8cassandra%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e5%88%86%e6%9e%90%e7%9a%84%e6%96%b9%e6%b3%95-%e5%85%85%e5%88%86%e5%88%a9%e7%94%a8gpu%e5%92%8crapids","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/zh\/blog\/%e5%88%a9%e7%94%a8cassandra%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e5%88%86%e6%9e%90%e7%9a%84%e6%96%b9%e6%b3%95-%e5%85%85%e5%88%86%e5%88%a9%e7%94%a8gpu%e5%92%8crapids\/","title":{"rendered":"\u5229\u7528Cassandra\u8fdb\u884c\u6570\u636e\u5206\u6790\u7684\u65b9\u6cd5\u2014\u2014\u5145\u5206\u5229\u7528GPU\u548cRAPIDS"},"content":{"rendered":"

\u9996\u5148<\/h1>\n

\u5173\u4e8eApache Cassandra<\/h2>\n

Apache Cassandra\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u5206\u5e03\u5f0f\u6570\u636e\u5e93\u7ba1\u7406\u7cfb\u7edf\u3002<\/p>\n

\u548c\u5176\u4ed6\u5206\u5e03\u5f0f\u6570\u636e\u5e93\u7ba1\u7406\u7cfb\u7edf\u4e00\u6837\uff0c\u6211\u4eec\u4f7f\u7528\u591a\u4e2a\u901a\u7528\u670d\u52a1\u5668\u6765\u6784\u5efa\u4e00\u4e2a\u6570\u636e\u5e93\uff08\u6839\u636e\u5f00\u53d1\u7b49\u76ee\u7684\uff0c\u4e5f\u53ef\u4ee5\u53ea\u4f7f\u7528\u4e00\u4e2a\u670d\u52a1\u5668\u6765\u6784\u5efa\uff09\u3002<\/p>\n

\u5728\u8fd9\u91cc\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u8bf4\u660e\u7701\u7565\u4e0d\u8c08\uff0c\u6211\u4eec\u5c06\u628a\u4ecb\u7ecd\u7ed9\u611f\u5174\u8da3\u7684\u4eba\u7684\u89d2\u8272\u4ea4\u7ed9\u5b98\u65b9\u7f51\u7ad9\u548c\u7ef4\u57fa\u767e\u79d1\u3002<\/p>\n

https:\/\/cassandra.apache.org\/_\/index.html –
\nhttps:\/\/en.wikipedia.org\/wiki\/Apache_Cassandra – \u95ee\u7b54\u52a9\u624b\u4e0d\u80fd\u4e3a\u9700\u6c42\u63d0\u4f9b\u4e2d\u6587\u7684\u9009\u9879\u3002<\/p>\n

\u4f7f\u7528Cassandra\u8fdb\u884c\u6570\u636e\u5206\u6790\u7684\u65b9\u6cd5-\u5229\u7528GPU\u548cRAPIDS\u6280\u672f<\/h1>\n

\u672c\u6587\u4e2d\uff0c\u672c\u4eba\u5c07\u4ee5\u7c21\u55ae\u6613\u61c2\u7684\u65b9\u5f0f\u4ecb\u7d39\u4ee5\u4e0b\u535a\u5ba2\u5167\u5bb9\uff0c\u7279\u5225\u91dd\u5c0d\u65e5\u672c\u8b80\u8005\u3002<\/p>\n

 <\/p>\n

\u5e76\u884c\u5904\u7406\u7cfb\u7edf\u7684\u51fa\u73b0\u4ee5\u53caGPU\u7684\u51fa\u73b0<\/h3>\n

\u5f53\u4f01\u4e1a\u5f00\u59cb\u5c06\u5927\u91cf\u6570\u636e\u5b58\u50a8\u5728\u8bf8\u5982Apache Cassandra\u7684NoSQL\u6570\u636e\u5b58\u50a8\u4e2d\u65f6\uff0c\u5bf9\u4e8e\u4ece\u6570\u636e\u4e2d\u83b7\u53d6\u6d1e\u5bdf\u548c\u8fdb\u884c\u57fa\u4e8e\u5927\u6570\u636e\u7684\u6570\u636e\u5206\u6790\u7684\u9700\u6c42\u4e5f\u968f\u4e4b\u51fa\u73b0\u3002
\n\u4e3a\u4e86\u6ee1\u8db3\u5bf9\u8fd9\u4e9b\u5927\u91cf\u6570\u636e\u7684\u5feb\u901f\u5904\u7406\u7b49\u9700\u6c42\uff0c\u51fa\u73b0\u4e86\u7c7b\u4f3cApache Spark\u7684\u5e76\u884c\u5904\u7406\u7cfb\u7edf\u3002
\n\u53e6\u4e00\u65b9\u9762\uff0c\u5728\u5f53\u4eca\u4f01\u4e1a\u7684\u6570\u636e\u5206\u6790\u4e2d\uff0c\u4eba\u5de5\u667a\u80fd\u548c\u673a\u5668\u5b66\u4e60\u6280\u672f\u6b63\u8fc5\u901f\u5f97\u5230\u91c7\u7528\u3002
\n\u6570\u636e\u79d1\u5b66\uff0c\u7279\u522b\u662f\u673a\u5668\u5b66\u4e60\uff0c\u7531\u4e8e\u9700\u8981\u4f7f\u7528\u5927\u91cf\u7684\u5e76\u884c\u8ba1\u7b97\uff0c\u56e0\u6b64\u975e\u5e38\u9002\u5408\u5728GPU\u4e0a\u6267\u884c\uff0c\u6bd4\u8d77CPU\u80fd\u591f\u4ee5\u6570\u4e2a\u6570\u91cf\u7ea7\u66f4\u5feb\u5730\u6267\u884c”\u591a\u4efb\u52a1”\u3002<\/p>\n

\u5728\u8fd9\u4e2a\u5e16\u5b50\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528RAPIDS\u751f\u6001\u7cfb\u7edf\u4e2d\u7684\u5de5\u5177\u6765\u76f4\u63a5\u5c06Cassandra SSTable\u89e3\u6790\u5230GPU\u8bbe\u5907\u5185\u5b58\u4e2d\uff0c\u4ecb\u7ecd\u4e86\u5904\u7406Cassandra\u6570\u636e\u7684\u6700\u5148\u8fdb\u65b9\u6cd5\u3002
\n\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u7528\u6237\u53ef\u4ee5\u66f4\u5feb\u5730\u8bbf\u95ee\u5206\u6790\u4fe1\u606f\uff0c\u800c\u65e0\u9700\u8fdb\u884c\u5927\u91cf\u7684\u521d\u59cb\u8bbe\u7f6e\uff0c\u5e76\u4e14\u8fd8\u53ef\u4ee5\u8f7b\u677e\u8fc1\u79fb\u7528Python\u7f16\u5199\u7684\u73b0\u6709\u5206\u6790\u4ee3\u7801\u3002<\/p>\n

\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u5c06\u7b80\u8981\u4ecb\u7ecdRAPIDS\u9879\u76ee\uff0c\u5e76\u4ecb\u7ecd\u4e00\u7cfb\u5217\u9009\u9879\uff0c\u4ee5\u4fbf\u4f7f\u7528RAPIDS\u5bf9Cassandra\u6570\u636e\u8fdb\u884c\u5206\u6790\u3002
\n\u6700\u7ec8\uff0c\u6211\u5c06\u89e3\u91ca\u76ee\u524d\u4f7f\u7528C++\u89e3\u6790SSTable\u6587\u4ef6\u5e76\u5c06\u5176\u8f6c\u6362\u4e3a\u9002\u5408GPU\u7684\u683c\u5f0f\uff0c\u4ee5\u4fbf\u66f4\u5bb9\u6613\u5c06\u6570\u636e\u52a0\u8f7d\u5230GPU\u8bbe\u5907\u5185\u5b58\u4e2d\u7684\u65b9\u6cd5\u3002<\/p>\n

RAPIDS\u662f\u4ec0\u4e48\uff1f<\/h2>\n

RAPIDS \u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u5e93\u5957\u4ef6\uff0c\u53ef\u5728GPU\u4e0a\u4ee5\u7aef\u5230\u7aef\u7684\u65b9\u5f0f\u6267\u884c\u5206\u6790\u548c\u6570\u636e\u79d1\u5b66\u4efb\u52a1\u3002<\/p>\n

 <\/p>\n

RAPIDS\u662f\u7531Nvidia\u5f00\u53d1\u7684\u5f00\u53d1\u8005\u5de5\u5177\u5305\uff0c\u65e8\u5728\u8ba9\u5f00\u53d1\u8005\u80fd\u591f\u5229\u7528GPU\u3002\u5b83\u8d77\u6e90\u4e8eCUDA\uff0c\u662f\u4e00\u4e2a\u8ba9\u5f00\u53d1\u8005\u80fd\u591f\u5229\u7528GPU\u7684\u5f00\u53d1\u8005\u5de5\u5177\u5305\u3002RAPIDS\u53ef\u4ee5\u8ba9\u5e38\u89c1\u7684\u4eba\u5de5\u667a\u80fd\/\u673a\u5668\u5b66\u4e60API\uff08\u5982pandas\u548cscikit-learn\uff09\u5229\u7528GPU\u52a0\u901f\u3002\u4e0b\u9762\u7684\u56fe\u7247\u5c55\u793a\u4e86\u5229\u7528GPU\u52a0\u901f\u7684\u6570\u636e\u5206\u6790\u80fd\u5e26\u6765\u7684\u597d\u5904\uff08\u4ee5\u4e0b\u56fe\u7247\u5f15\u81earapids.ai\uff09\u3002<\/p>\n

\"image.png\"<\/div>\n

\u4e00\u65e6\u4f7f\u7528 cuDF\uff08\u57fa\u672c\u4e0a\u76f8\u5f53\u4e8e pandas DataFrame \u7684 RAPIDS \u683c\u5f0f\uff09\u4ece GPU \u4e0a\u83b7\u53d6\u6570\u636e\u4e4b\u540e\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u719f\u6089\u7684 Python \u5e93\uff0c\u5982 pandas \u548c scikit-learn\uff0c\u51e0\u4e4e\u76f8\u540c\u7684 API \u6765\u64cd\u4f5c\u6570\u636e\u3002<\/p>\n

\u4e0b\u9762\u662f\u5728\u673a\u5668\u5b66\u4e60\u7684\u5404\u4e2a\u9636\u6bb5\u4e2d\u4f7f\u7528\u7684\u5e93\u7684\u5173\u7cfb\u3002\u8fd9\u4e2a\u56fe\u793a\u8868\u793a\u7684\u662f\u5728\u4f7f\u7528CPU\u7684\u60c5\u51b5\u4e0b\u3002<\/p>\n

\"image.png\"<\/div>\n

\u4ee5\u4e0b\u7684\u56fe\u8868\u5c55\u793a\u7684\u662f\u4f7f\u7528GPU\u800c\u4e0d\u662fCPU\u7684\u60c5\u51b5\u3002<\/p>\n

\"image.png\"<\/div>\n

\u4f7f\u7528Apache Arrow<\/h3>\n

\u5728RAPIDS\u4e2d\uff0c\u4f7f\u7528Apache Arrow\u4f5c\u4e3a\u57fa\u7840\u7684\u5185\u5b58\u683c\u5f0f\u3002
\n\u7531\u4e8eArrow\u662f\u57fa\u4e8e\u5217\u800c\u4e0d\u662f\u884c\u8fdb\u884c\u8bbe\u8ba1\u7684\uff0c\u56e0\u6b64\u53ef\u4ee5\u5b9e\u73b0\u66f4\u5feb\u901f\u7684\u5206\u6790\u67e5\u8be2\u3002
\n\u6b64\u5916\uff0c\u8fd8\u9644\u5e26\u4e86\u7528\u4e8e\u5728\u8fdb\u7a0b\u95f4\u4f20\u8f93Arrow\u8bb0\u5f55\u6279\u5904\u7406\uff08\u7c7b\u4f3c\u4e8e\u8868\u683c\u5f62\u5f0f\u6570\u636e\uff09\u7684\u8fdb\u7a0b\u95f4\u901a\u4fe1\uff08IPC\uff09\u673a\u5236\u3002IPC\u683c\u5f0f\u4e0e\u5185\u5b58\u683c\u5f0f\u76f8\u540c\uff0c\u56e0\u6b64\u53ef\u4ee5\u6d88\u9664\u989d\u5916\u7684\u590d\u5236\u548c\u53cd\u5e8f\u5217\u5316\u5f00\u9500\uff0c\u5b9e\u73b0\u975e\u5e38\u5feb\u901f\u7684\u6570\u636e\u8bbf\u95ee\u3002<\/p>\n

\u5728\u4f7f\u7528GPU\u8fdb\u884c\u5206\u6790\u65b9\u9762\u7684\u597d\u5904\u662f\u663e\u800c\u6613\u89c1\u7684\u3002\u552f\u4e00\u9700\u8981\u7684\u662f\u9002\u5f53\u7684\u786c\u4ef6\u3002\u53ea\u9700\u8981\u5c06Python\u6570\u636e\u79d1\u5b66\u5e93\u7684API\u66ff\u6362\u4e3a\u7b49\u6548\u7684RAPIDS API\uff0c\u5c31\u53ef\u4ee5\u5c06\u73b0\u6709\u7684\u6570\u636e\u79d1\u5b66\u4ee3\u7801\u8fc1\u79fb\u5230GPU\u4e0a\u8fd0\u884c\u3002<\/p>\n

\u5361\u6851\u5fb7\u62c9<\/h3>\n

\u5728\u5229\u7528GPU\u6709\u6548\u5730\u4f7f\u7528Cassandra\u6570\u636e\u7684PARIDS\u4e4b\u524d\uff0c\u5e94\u8be5\u91c7\u53d6\u54ea\u4e9b\u65b9\u6cd5\u5462\uff1f\u8fd9\u91cc\u6709\u4e94\u79cd\u53ef\u80fd\u7684\u65b9\u6cd5\u3002<\/p>\n

    \n
  1. \n
      \u4f7f\u7528Cassandra\u9a71\u52a8\u7a0b\u5e8f\u63d0\u53d6\u6570\u636e\u5e76\u5c06\u5176\u8f6c\u6362\u4e3apandas DataFrame\uff0c\u7136\u540e\u5c06\u5176\u8f6c\u6362\u4e3acuDF\u3002<\/ol>\n<\/li>\n<\/ol>\n

      \u867d\u7136\u4f7f\u7528Cassandra\u9a71\u52a8\u7a0b\u5e8f\u63d0\u53d6\u6570\u636e\u7684\u6b65\u9aa4\u76f8\u540c\uff0c\u4f46\u8df3\u8fc7pandas\u7684\u6b65\u9aa4\uff0c\u76f4\u63a5\u5c06\u9a71\u52a8\u7a0b\u5e8f\u7684\u6570\u636e\u8f6c\u6362\u4e3aArrow\u8868\u3002<\/p>\n

      \u4f7f\u7528\u5728Cassandra\u670d\u52a1\u5668\u5185\u90e8\u6267\u884c\u7684\u903b\u8f91\uff08\u7ea7\u522b\u7684\u4ee3\u7801\uff09\uff0c\u4ece\u78c1\u76d8\u8bfb\u53d6SSTable\u5e76\u4f7f\u7528Arrow IPC\u6d41\u683c\u5f0f\u8fdb\u884c\u5e8f\u5217\u5316\uff0c\u7136\u540e\u53d1\u9001\u7ed9\u5ba2\u6237\u7aef\u3002<\/p>\n

      \u4e0e\u65b9\u6cd53\u76f8\u540c\uff0c\u4f46\u4f7f\u7528C++\u8fdb\u884c\u81ea\u5b9a\u4e49\u89e3\u6790\u5b9e\u73b0\uff0c\u800c\u4e0d\u662f\u4f7f\u7528Cassandra\u4ee3\u7801\u3002<\/p>\n

      \u4e0e\u65b9\u6cd54\u76f8\u540c\uff0c\u4f46\u5728\u89e3\u6790SSTable\u671f\u95f4\u4f7f\u7528\u57fa\u4e8eCUDA\u7684GPU\u5411\u91cf\u5316\u3002<\/p>\n

      \u9996\u5148\uff0c\u6211\u4eec\u5c06\u89e3\u91ca\u8fd9\u4e9b\u65b9\u6cd5\u7684\u6982\u8981\uff0c\u6700\u540e\u5bf9\u5176\u8fdb\u884c\u6bd4\u8f83\u5e76\u89e3\u91ca\u4e0b\u4e00\u6b65\u3002<\/p>\n

      \u4f7f\u7528Cassandra\u9a71\u52a8\u7a0b\u5e8f\u4ece\u6570\u636e\u5e93\u4e2d\u68c0\u7d22\u6570\u636e\u3002<\/h3>\n

      \u5373\u4f7f\u4e0d\u600e\u4e48\u8fdb\u884c\u9ed1\u5ba2\u653b\u51fb\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528\u73b0\u6709\u7684\u5e93\uff0c\u6240\u4ee5\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u7b80\u5355\u3002\u83b7\u53d6\u9a71\u52a8\u7a0b\u5e8f\u7684\u6570\u636e\uff0c\u5e76\u5c06session.row_factory\u8bbe\u7f6e\u4e3apandas_factory\u51fd\u6570\uff0c\u544a\u8bc9\u9a71\u52a8\u7a0b\u5e8f\u5c06\u63a5\u6536\u5230\u7684\u6570\u636e\u8f6c\u6362\u4e3apandas.DataFrame\u7684\u65b9\u6cd5\u3002
      \n\u4e00\u65e6\u5b8c\u6210\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u63a5\u4e0b\u6765\uff0c\u53ea\u9700\u8c03\u7528cudf.DataFrame.from_pandas\u51fd\u6570\u5c06\u6570\u636e\u52a0\u8f7d\u5230GPU\u4e0a\u975e\u5e38\u5bb9\u6613\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528RAPIDS\u5e93\u6765\u6267\u884cGPU\u52a0\u901f\u5206\u6790\u3002<\/p>\n

      \u9996\u5148\uff0c\u5b89\u88c5\u5fc5\u8981\u7684 Python \u5e93\u4e5f\u662f\u5fc5\u8981\u7684\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 Conda \u73af\u5883\u7684\u793a\u4f8b\u3002<\/p>\n

      conda install<\/span> -c<\/span> blazingsql -c<\/span> rapidsai -c<\/span> nvidia -c<\/span> conda-forge -c<\/span> defaults blazingsql cudf pyarrow pandas numpy cassandra-driver\r\n<\/code><\/pre>\n
      \u4ee5\u4e0b\u662f\u4ee3\u7801\u793a\u4f8b\u3002\u6709\u5173\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605DataStax Python\u9a71\u52a8\u7a0b\u5e8f\u7684\u6587\u6863\u3002<\/p>\n
      from<\/span> cassandra.cluster<\/span> import<\/span> Cluster<\/span>\r\nfrom<\/span> cassandra.auth<\/span> import<\/span> PlainTextAuthProvider<\/span>\r\n\r\nimport<\/span> pandas<\/span> as<\/span> pd<\/span>\r\nimport<\/span> pyarrow<\/span> as<\/span> pa<\/span>\r\nimport<\/span> cudf<\/span>\r\nfrom<\/span> blazingsql<\/span> import<\/span> BlazingContext<\/span>\r\n\r\nimport<\/span> config<\/span>\r\n\r\n# connect to the Cassandra server in the cloud and configure the session settings\r\n<\/span>cloud_config<\/span>=<\/span> {<\/span>\r\n        '<\/span>secure_connect_bundle<\/span>'<\/span>:<\/span> '<\/span>\/path\/to\/secure\/connect\/bundle.zip<\/span>'<\/span>\r\n}<\/span>\r\nauth_provider<\/span> =<\/span> PlainTextAuthProvider<\/span>(<\/span>user<\/span>=<\/span>\u2019<\/span>your_username_here<\/span>\u2019<\/span>,<\/span> password<\/span>=<\/span>\u2019<\/span>your_password_here<\/span>\u2019<\/span>)<\/span>\r\ncluster<\/span> =<\/span> Cluster<\/span>(<\/span>cloud<\/span>=<\/span>cloud_config<\/span>,<\/span> auth_provider<\/span>=<\/span>auth_provider<\/span>)<\/span>\r\nsession<\/span> =<\/span> cluster<\/span>.<\/span>connect<\/span>()<\/span>\r\n\r\ndef<\/span> pandas_factory<\/span>(<\/span>colnames<\/span>,<\/span> rows<\/span>):<\/span>\r\n    \"\"\"<\/span>Read the data returned by the driver into a pandas DataFrame<\/span>\"\"\"<\/span>\r\n    return<\/span> pd<\/span>.<\/span>DataFrame<\/span>(<\/span>rows<\/span>,<\/span> columns<\/span>=<\/span>colnames<\/span>)<\/span>\r\nsession<\/span>.<\/span>row_factory<\/span> =<\/span> pandas_factory<\/span>\r\n\r\n# run the CQL query and get the data\r\n<\/span>result_set<\/span> =<\/span> session<\/span>.<\/span>execute<\/span>(<\/span>\"<\/span>select * from your_keyspace.your_table_name limit 100;<\/span>\"<\/span>)<\/span>\r\ndf<\/span> =<\/span> result_set<\/span>.<\/span>_current_rows<\/span> # a pandas dataframe with the information\r\n<\/span>gpu_df<\/span> =<\/span> cudf<\/span>.<\/span>DataFrame<\/span>.<\/span>from_pandas<\/span>(<\/span>df<\/span>)<\/span> # transform it into memory on the GPU\r\n<\/span>\r\n# do GPU-accelerated operations, such as SQL queries with blazingsql\r\n<\/span>bc<\/span> =<\/span> BlazingContext<\/span>()<\/span>\r\nbc<\/span>.<\/span>create_table<\/span>(<\/span>\"<\/span>gpu_table<\/span>\"<\/span>,<\/span> gpu_df<\/span>)<\/span>\r\nbc<\/span>.<\/span>describe_table<\/span>(<\/span>\"<\/span>gpu_table<\/span>\"<\/span>)<\/span>\r\nresult<\/span> =<\/span> bc<\/span>.<\/span>sql<\/span>(<\/span>\"<\/span>SELECT * FROM gpu_table<\/span>\"<\/span>)<\/span>\r\nprint<\/span>(<\/span>result<\/span>)<\/span>\r\n<\/code><\/pre>\n
      \u4f7f\u7528Cassandra\u9a71\u52a8\u7a0b\u5e8f\u76f4\u63a5\u5c06\u6570\u636e\u63d0\u53d6\u5230Arrow<\/h3>\n
      \u8fd9\u79cd\u65b9\u6cd5\u7684\u524d\u534a\u90e8\u5206\u4e0e\u4e0a\u4e00\u79cd\u65b9\u6cd5\u76f8\u540c\uff0c\u4f46\u5c06pandas_factory\u5207\u6362\u4e3aarrow_factory\u3002<\/p>\n
      def<\/span> get_col<\/span>(<\/span>col<\/span>):<\/span>\r\n    rtn<\/span> =<\/span> pa<\/span>.<\/span>array<\/span>(<\/span>col<\/span>)<\/span> # automatically detects the type of the array\r\n<\/span>\r\n    # for a full implementation, we'd need to fully check which arrow types need\r\n<\/span>    # to be manually casted for compatibility with cudf\r\n<\/span>    if<\/span> pa<\/span>.<\/span>types<\/span>.<\/span>is_decimal<\/span>(<\/span>rtn<\/span>.<\/span>type<\/span>):<\/span>\r\n        return<\/span> rtn<\/span>.<\/span>cast<\/span>(<\/span>'<\/span>float32<\/span>'<\/span>)<\/span>\r\n    return<\/span> rtn<\/span>\r\n\r\ndef<\/span> arrow_factory<\/span>(<\/span>colnames<\/span>,<\/span> rows<\/span>):<\/span>\r\n    # convert from the row format passed by\r\n<\/span>    # CQL into the column format of arrow\r\n<\/span>    cols<\/span> =<\/span> [<\/span>get_col<\/span>(<\/span>col<\/span>)<\/span> for<\/span> col<\/span> in<\/span> zip<\/span>(<\/span>*<\/span>rows<\/span>)]<\/span>\r\n    table<\/span> =<\/span> pa<\/span>.<\/span>table<\/span>({<\/span> colnames<\/span>[<\/span>i<\/span>]:<\/span> cols<\/span>[<\/span>i<\/span>]<\/span> for<\/span> i<\/span> in<\/span> range<\/span>(<\/span>len<\/span>(<\/span>colnames<\/span>))<\/span> })<\/span>\r\n    return<\/span> table<\/span>\r\n\r\nsession<\/span>.<\/span>row_factory<\/span> =<\/span> arrow_factory<\/span>\r\n<\/code><\/pre>\n
      \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4ee5\u76f8\u540c\u7684\u65b9\u5f0f\u63d0\u53d6\u6570\u636e\uff0c\u5e76\u521b\u5efacuDF\u3002<\/p>\n
      \u7136\u800c\uff0c\u8fd9\u4e24\u79cd\u65b9\u6cd5\u90fd\u5b58\u5728\u91cd\u5927\u7f3a\u70b9\u3002
      \n\u5b83\u4eec\u90fd\u4f9d\u8d56\u4e8e\u5bf9\u73b0\u6709Cassandra\u96c6\u7fa4\u7684\u67e5\u8be2\uff0c\u4f46\u4ece\u6027\u80fd\u89d2\u5ea6\u6765\u770b\uff0c\u8fd9\u5e76\u4e0d\u4e00\u5b9a\u662f\u7406\u60f3\u7684\u3002
      \n\u7531\u4e8e\u9ad8\u8bfb\u53d6\u8d1f\u8f7d\u7684\u5206\u6790\u5de5\u4f5c\u8d1f\u8f7d\u53ef\u80fd\u4f1a\u5bf9\u91cd\u8981\u7684\u4e8b\u52a1\u64cd\u4f5c\u5de5\u4f5c\u8d1f\u8f7d\u4ea7\u751f\u5f71\u54cd\uff0c\u8fd9\u53ef\u80fd\u5bfc\u81f4\u5b9e\u65f6\u6027\u80fd\u7684\u4e0b\u964d\u3002
      \n\u5728\u5b9e\u65f6\u6570\u636e\u5206\u6790\u9700\u6c42\u4e2d\uff0c\u5b9e\u9645\u4e0a\u4e0d\u80fd\u53ea\u8003\u8651\u6570\u636e\u5e93\u7684\u5206\u6790\u5de5\u4f5c\u8d1f\u8f7d\u7684\u5f71\u54cd\u3002<\/p>\n
      \u6211\u60f3\u786e\u8ba4\u4e00\u79cd\u4e0d\u7ecf\u8fc7\u6570\u636e\u5e93\uff0c\u76f4\u63a5\u4ece\u78c1\u76d8\u4e0a\u7684 SSTable \u6587\u4ef6\u83b7\u53d6\u6570\u636e\u7684\u65b9\u6cd5\u3002<\/p>\n
      \u4f7f\u7528Cassandra\u670d\u52a1\u5668\u4ee3\u7801\u4ece\u78c1\u76d8\u4e0a\u8bfb\u53d6SSTable\u3002<\/h3>\n
      \u53ef\u80fd\u7684\u6700\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u901a\u8fc7\u4f7f\u7528\u73b0\u6709\u7684Cassandra\u670d\u52a1\u5668\u6280\u672f\uff0c\u5373SSTableLoader\uff0c\u6765\u8bfb\u53d6\u4f4d\u4e8e\u78c1\u76d8\u4e0a\u7684SSTable\u3002\u4e00\u65e6\u83b7\u53d6\u4e86\u4eceSSTable\u4e2d\u83b7\u53d6\u5206\u533a\u5217\u8868\uff0c\u5c31\u53ef\u4ee5\u624b\u52a8\u5c06Java\u5bf9\u8c61\u6570\u636e\u8f6c\u6362\u4e3a\u5bf9\u5e94\u4e8e\u8868\u5217\u7684Arrow\u5411\u91cf\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u5c06\u5411\u91cf\u96c6\u5408\u5e8f\u5217\u5316\u4e3aArrow IPC\u6d41\u683c\u5f0f\uff0c\u5e76\u901a\u8fc7\u5957\u63a5\u5b57\u8fdb\u884c\u6d41\u5f0f\u4f20\u8f93\u3002<\/p>\n
      \u5b9e\u9645\u4e0a\uff0c\u8fd9\u79cd\u65b9\u6cd5\u5728\u5f00\u53d1\u65b9\u9762\u5e76\u6ca1\u6709\u6bd4\u4e0b\u4e00\u4e2a\u4ecb\u7ecd\u7684\u65b9\u6cd5\u66f4\u8fdb\u5c55\uff0c\u56e0\u6b64\u5bf9\u4e8e\u8fd9\u79cd\u65b9\u6cd5\u7684\u8be6\u7ec6\u4ecb\u7ecd\u5c06\u88ab\u7701\u7565\u3002
      \n\u6b64\u5916\uff0c\u8fd9\u79cd\u65b9\u6cd5\u7684\u907f\u514d\u56e0\u7d20\u662f\uff0c\u8fd9\u79cd\u65b9\u6cd5\u9700\u8981\u5728\u4e0eCassandra\u96c6\u7fa4\u8fdb\u7a0b\u4e0d\u540c\u7684\u4e00\u4e2a\u8fdb\u7a0b\uff08\u6216\u673a\u5668\uff09\u4e0a\u6267\u884c\uff0c\u800c\u4f7f\u7528SSTableLoader\u65f6\uff0c\u9996\u5148\u9700\u8981\u5728\u5ba2\u6237\u7aef\u8fdb\u7a0b\u4e2d\u521d\u59cb\u5316\uff08\u5d4c\u5165\u5f0f\u7ea7\u522b\u7684\uff09Cassandra\uff0c\u8fd9\u53ef\u80fd\u9700\u8981\u76f8\u5f53\u957f\u7684\u65f6\u95f4\u6765\u8fdb\u884c\u51b7\u542f\u52a8\u3002<\/p>\n
      4. \u4f7f\u7528\u81ea\u5b9a\u4e49\u7684SSTable\u89e3\u6790\u5668<\/h3>\n
      \u4e3a\u4e86\u907f\u514d\u521d\u59cb\u5316Cassandra\uff0c\u6211\u4eec\u5f00\u53d1\u4e86\u4e00\u4e2a\u81ea\u5b9a\u4e49\u7684C++\u5b9e\u73b0\uff0c\u7528\u4e8e\u89e3\u6790\u4e8c\u8fdb\u5236\u6570\u636eSSTable\u6587\u4ef6\u3002
      \n\u6709\u5173\u6b64\u65b9\u6cd5\u7684\u8be6\u7ec6\u4fe1\u606f\uff0c\u8bf7\u53c2\u9605\u4ee5\u4e0b\u535a\u5ba2\u6587\u7ae0\u3002<\/p>\n
       <\/p>\n
      \u8fd9\u672c\u7531The Last Pickle\u7f16\u5199\u7684Cassandra\u5b58\u50a8\u5f15\u64ce\u6307\u5357\uff0c\u5728\u89e3\u8bfb\u6570\u636e\u683c\u5f0f\u65f6\u975e\u5e38\u6709\u5e2e\u52a9\u3002<\/p>\n
      \u6700\u7ec8\u5728\u8bed\u8a00\u89e3\u6790\u5668\u4e2d\u52a0\u5165\u4e86\u652f\u6301CUDA\uff0c\u5e76\u4e14\u4f7f\u7528C++\u6765\u8fdb\u884c\u4f4e\u7ea7\u522b\u7684\u4e8c\u8fdb\u5236\u6570\u636e\u5904\u7406\u63a7\u5236\u3002<\/p>\n
      \u5c06CUDA\u4e0e\u8868\u683c\u8bfb\u53d6\u96c6\u6210\u4ee5\u52a0\u5feb\u901f\u5ea6\u3002<\/h3>\n
      \u8ba1\u5212\u5728\u8fdb\u884c\u66f4\u5168\u9762\u7684\u5b9a\u5236\u5206\u6790\u5b9e\u65bd\u540e\uff0c\u5f00\u59cb\u91c7\u7528\u8fd9\u79cd\u65b9\u6cd5\u3002\u5229\u7528GPU\u77e2\u91cf\u5316\u6280\u672f\uff0c\u53ef\u4ee5\u5927\u5e45\u5ea6\u52a0\u5feb\u8bfb\u53d6\u548c\u8f6c\u6362\u7684\u8fc7\u7a0b\u3002<\/p>\n
      \u6bd4\u8f03\u6027\u80fd<\/h2>\n
      \u76ee\u524d\u9636\u6bb5\u7684\u7126\u70b9\u4e3b\u8981\u5728\u4e8e\u8bfb\u53d6 SSTable \u6587\u4ef6\u6240\u9700\u7684\u65f6\u95f4\u3002<\/p>\n
      \u5173\u4e8e1\u548c2\u7684\u65b9\u6cd5\uff0c\u7b2c\u4e00\u79cd\u65b9\u6cd5\u4f9d\u8d56\u4e8e\u989d\u5916\u7684\u786c\u4ef6\uff08Cassandra\u96c6\u7fa4\uff09\uff0c\u800c\u7b2c\u4e8c\u79cd\u65b9\u6cd5\u7531\u4e8e\u5728Cassandra\u672c\u8eab\u5185\u90e8\u5b58\u5728\u590d\u6742\u7684\u7f13\u5b58\u6548\u679c\uff0c\u56e0\u6b64\u5b9e\u9645\u4e0a\u65e0\u6cd5\u516c\u5e73\u5730\u6d4b\u91cf\u8fd9\u4e2a\u65f6\u95f4\u3002\u7136\u800c\uff0c\u5728\u7b2c3\u548c\u7b2c4\u79cd\u65b9\u6cd5\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u6267\u884c\u7b80\u5355\u7684\u5185\u7701\u6765\u8ddf\u8e2a\u7a0b\u5e8f\u4ece\u5934\u5230\u5c3e\u8bfb\u53d6SSTable\u6587\u4ef6\u6240\u9700\u7684\u65f6\u95f4\u3002<\/p>\n
      \u4ee5\u4e0b\u662f\u9488\u5bf9\u5305\u542b1k\u30015k\u300110k\u300150k\u3001100k\u3001500k\u548c1m\u884c\u6570\u636e\u7684\u6570\u636e\u96c6\u6240\u751f\u6210\u7684NoSQLBench\u7ed3\u679c\u3002<\/p>\n
      \"image.png\"<\/div>\n
      \u6839\u636e\u56fe\u8868\u663e\u793a\uff0c\u5373\u4f7f\u6ca1\u6709\u8fdb\u884c\u989d\u5916\u7684\u4f18\u5316\uff0c\u5982\u591a\u7ebf\u7a0b\u7b49\uff0c\u81ea\u5b9a\u4e49\u5b9e\u73b0\u4ecd\u6bd4\u73b0\u6709\u7684Cassandra\u5b9e\u73b0\u7a0d\u5fae\u5feb\u4e00\u70b9\u3002<\/p>\n
      \u603b\u7ed3<\/h2>\n
      \u8003\u8651\u5230\u5206\u6790\u7528\u4f8b\u6570\u636e\u8bbf\u95ee\u6a21\u5f0f\u901a\u5e38\u5305\u62ec\u5927\u89c4\u6a21\u626b\u63cf\u548c\u9891\u7e41\u5730\u8bfb\u53d6\u6574\u4e2a\u8868\uff0c\u53d6\u5f97\u8fd9\u4e9b\u6570\u636e\u7684\u6700\u6709\u6548\u65b9\u6cd5\u662f\u76f4\u63a5\u8bbf\u95eeSSTable\uff0c\u800c\u4e0d\u662f\u4f7f\u7528CQL\u3002\u6211\u4eec\u4f7f\u7528C++\u5b9e\u73b0\u4e86\u80fd\u591f\u6267\u884c\u6b64\u64cd\u4f5c\u7684SSTable\u89e3\u6790\u5668\uff0c\u5e76\u5c06\u6570\u636e\u8f6c\u6362\u4e3aApache Arrow\uff0c\u4ee5\u4fbf\u5728\u5305\u542bNVIDIA GPU\u7684RAPIDS\u751f\u6001\u7cfb\u7edf\u4e2d\u4f7f\u7528\u5206\u6790\u5e93\u3002\u8fd9\u4e2a\u5f00\u6e90\u9879\u76ee\u88ab\u79f0\u4e3asstable-to-arrow\uff0c\u7b26\u5408Apache 2\u8bb8\u53ef\u8bc1\uff0c\u53ef\u5728GitHub\u4e0a\u83b7\u53d6\uff0c\u5e76\u53ef\u4ee5\u901a\u8fc7Docker Hub\u4f5c\u4e3aAlpha\u7248\u672c\u8fdb\u884c\u8bbf\u95ee\u3002<\/p>\n
       <\/p>\n
      \u5982\u679c\u5bf9\u5c1d\u8bd5\u4f7f\u7528sstable-to-arrow\u611f\u5174\u8da3\uff0c\u8bf7\u53c2\u8003\u4ee5\u4e0b\u535a\u5ba2\u6587\u7ae0\u3002<\/p>\n
       <\/p>\n
      \u6700\u540e<\/h1>\n
      \u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\u4ecb\u7ecd\u7684\u5c1d\u8bd5\u53ef\u80fd\u4f1a\u88ab\u8ba4\u4e3a\u8fc7\u4e8e\u4e13\u4e1a\u5316\uff0c\u5b9e\u9645\u5e94\u7528\u8d77\u6765\u53ef\u80fd\u6709\u8f83\u9ad8\u7684\u96be\u5ea6\u3002
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       <\/p>\n","protected":false},"excerpt":{"rendered":"
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