{"id":1043279,"date":"2024-12-31T13:04:49","date_gmt":"2024-12-31T05:04:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1043279.html"},"modified":"2024-12-31T13:04:51","modified_gmt":"2024-12-31T05:04:51","slug":"python%e5%a6%82%e4%bd%95%e5%a4%84%e7%90%86%e5%a4%a7%e8%a7%84%e6%a8%a1%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1043279.html","title":{"rendered":"python\u5982\u4f55\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/446fe327-11de-440a-9083-8e982b4dd7c0.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"python\u5982\u4f55\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\" \/><\/p>\n<p><p> <strong>Python\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u65b9\u5f0f\u5305\u62ec\uff1a\u4f7f\u7528Pandas\u5e93\u5904\u7406\u6570\u636e\u3001\u5229\u7528Dask\u5e93\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u3001\u91c7\u7528NumPy\u8fdb\u884c\u9ad8\u6548\u6570\u503c\u8fd0\u7b97\u3001\u4f7f\u7528PySpark\u8fdb\u884c\u5206\u5e03\u5f0f\u8ba1\u7b97\u3001\u57fa\u4e8eHDF5\u683c\u5f0f\u5b58\u50a8\u6570\u636e\u3002\u8fd9\u4e9b\u65b9\u6cd5\u5404\u6709\u4f18\u52a3\uff0c\u9002\u7528\u4e8e\u4e0d\u540c\u7684\u6570\u636e\u5904\u7406\u573a\u666f\u3002<\/strong> \u5176\u4e2d\uff0cPandas\u5e93\u5728\u5904\u7406\u4e2d\u5c0f\u89c4\u6a21\u6570\u636e\u65f6\u975e\u5e38\u5f3a\u5927\uff0cDask\u80fd\u591f\u8ba9Pandas\u7684\u64cd\u4f5c\u5e76\u884c\u5316\uff0c\u9002\u5408\u66f4\u5927\u89c4\u6a21\u7684\u6570\u636e\uff0c\u800cPySpark\u5219\u662f\u57fa\u4e8eApache Spark\u7684Python\u63a5\u53e3\uff0c\u80fd\u591f\u5904\u7406\u5206\u5e03\u5f0f\u6570\u636e\u8ba1\u7b97\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\u53ca\u5176\u5e94\u7528\u573a\u666f\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001PANDAS\u5e93\u5904\u7406\u6570\u636e<\/p>\n<\/p>\n<p><p>Pandas\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u548c\u64cd\u4f5c\u5e93\uff0c\u9002\u7528\u4e8e\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\u3002\u5b83\u63d0\u4f9b\u4e86\u6570\u636e\u5e27\uff08DataFrame\uff09\u8fd9\u4e00\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\uff0c\u4f7f\u5f97\u6570\u636e\u64cd\u4f5c\u53d8\u5f97\u7b80\u5355\u76f4\u89c2\u3002\u5bf9\u4e8e\u4e2d\u5c0f\u89c4\u6a21\u6570\u636e\uff0cPandas\u662f\u4e00\u4e2a\u7406\u60f3\u7684\u9009\u62e9\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u52a0\u8f7d\u548c\u64cd\u4f5c\u6570\u636e<\/h3>\n<\/p>\n<p><p>Pandas\u53ef\u4ee5\u8f7b\u677e\u5730\u4ece\u5404\u79cd\u6587\u4ef6\u683c\u5f0f\uff08\u5982CSV\u3001Excel\u3001SQL\u6570\u636e\u5e93\u7b49\uff09\u4e2d\u52a0\u8f7d\u6570\u636e\uff0c\u5e76\u652f\u6301\u591a\u79cd\u6570\u636e\u64cd\u4f5c\uff0c\u5982\u7b5b\u9009\u3001\u805a\u5408\u3001\u8fde\u63a5\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u52a0\u8f7dCSV\u6587\u4ef6<\/strong><\/h2>\n<p>df = pd.read_csv(&#39;data.csv&#39;)<\/p>\n<h2><strong>\u6570\u636e\u7b5b\u9009<\/strong><\/h2>\n<p>filtered_df = df[df[&#39;column_name&#39;] &gt; threshold]<\/p>\n<h2><strong>\u6570\u636e\u805a\u5408<\/strong><\/h2>\n<p>grouped_df = df.groupby(&#39;group_column&#39;).sum()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u9650\u5236<\/h3>\n<\/p>\n<p><p>\u7136\u800c\uff0cPandas\u5728\u5904\u7406\u7279\u522b\u5927\u89c4\u6a21\u7684\u6570\u636e\u65f6\u53ef\u80fd\u4f1a\u9047\u5230\u5185\u5b58\u9650\u5236\u95ee\u9898\u3002Pandas\u7684\u6570\u636e\u7ed3\u6784\u662f\u57fa\u4e8e\u5185\u5b58\u7684\uff0c\u8fd9\u610f\u5473\u7740\u5904\u7406\u7684\u6570\u636e\u91cf\u4e0d\u80fd\u8d85\u8fc7\u53ef\u7528\u5185\u5b58\u3002\u56e0\u6b64\uff0cPandas\u9002\u5408\u5904\u7406\u7684\u6570\u636e\u89c4\u6a21\u901a\u5e38\u5728\u6570\u767e\u4e07\u884c\u4ee5\u4e0b\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001DASK\u5e93\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97<\/p>\n<\/p>\n<p><p>Dask\u662f\u4e00\u4e2a\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u53ef\u4ee5\u6269\u5c55Pandas\u7684\u529f\u80fd\uff0c\u4f7f\u5176\u80fd\u591f\u5904\u7406\u66f4\u5927\u89c4\u6a21\u7684\u6570\u636e\u3002Dask\u5c06\u6570\u636e\u5206\u5272\u6210\u591a\u4e2a\u66f4\u5c0f\u7684\u5206\u5757\uff0c\u6bcf\u4e2a\u5206\u5757\u53ef\u4ee5\u72ec\u7acb\u5904\u7406\uff0c\u6700\u7ec8\u5408\u5e76\u7ed3\u679c\u3002<\/p>\n<\/p>\n<p><h3>1\u3001Dask DataFrame<\/h3>\n<\/p>\n<p><p>Dask DataFrame\u63d0\u4f9b\u4e86\u4e0ePandas\u7c7b\u4f3c\u7684\u63a5\u53e3\uff0c\u4f46\u5b83\u53ef\u4ee5\u5904\u7406\u6bd4\u5185\u5b58\u5927\u5f97\u591a\u7684\u6570\u636e\u96c6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import dask.dataframe as dd<\/p>\n<h2><strong>\u52a0\u8f7dCSV\u6587\u4ef6<\/strong><\/h2>\n<p>ddf = dd.read_csv(&#39;large_data.csv&#39;)<\/p>\n<h2><strong>\u6570\u636e\u7b5b\u9009<\/strong><\/h2>\n<p>filtered_ddf = ddf[ddf[&#39;column_name&#39;] &gt; threshold]<\/p>\n<h2><strong>\u6570\u636e\u805a\u5408<\/strong><\/h2>\n<p>grouped_ddf = ddf.groupby(&#39;group_column&#39;).sum().compute()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u4f18\u52bf\u4e0e\u5c40\u9650<\/h3>\n<\/p>\n<p><p><strong>Dask\u7684\u4e3b\u8981\u4f18\u52bf\u5728\u4e8e\u5176\u5e76\u884c\u8ba1\u7b97\u80fd\u529b<\/strong>\uff0c\u5b83\u53ef\u4ee5\u5229\u7528\u591a\u6838CPU\u548c\u96c6\u7fa4\u8d44\u6e90\u6765\u52a0\u901f\u6570\u636e\u5904\u7406\u3002\u7136\u800c\uff0cDask\u7684\u64cd\u4f5c\u901f\u5ea6\u901a\u5e38\u4e0d\u5982Pandas\u5feb\uff0c\u7279\u522b\u662f\u5728\u5c0f\u89c4\u6a21\u6570\u636e\u96c6\u4e0a\u3002\u56e0\u6b64\uff0cDask\u66f4\u9002\u5408\u5904\u7406\u8d85\u51fa\u5355\u673a\u5185\u5b58\u7684\u5927\u89c4\u6a21\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001NumPy\u8fdb\u884c\u9ad8\u6548\u6570\u503c\u8fd0\u7b97<\/p>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u5927\u91cf\u7684\u6570\u5b66\u51fd\u6570\u3002NumPy\u7684\u5e95\u5c42\u5b9e\u73b0\u4f7f\u7528\u4e86C\u8bed\u8a00\uff0c\u4f7f\u5176\u5728\u6570\u503c\u8ba1\u7b97\u65b9\u9762\u5177\u6709\u5f88\u9ad8\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<p><h3>1\u3001NumPy\u6570\u7ec4<\/h3>\n<\/p>\n<p><p>NumPy\u6570\u7ec4\uff08ndarray\uff09\u662f\u4e00\u4e2a\u9ad8\u6548\u7684\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\uff0c\u652f\u6301\u77e2\u91cf\u5316\u64cd\u4f5c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efaNumPy\u6570\u7ec4<\/strong><\/h2>\n<p>arr = np.random.rand(1000000)<\/p>\n<h2><strong>\u77e2\u91cf\u5316\u64cd\u4f5c<\/strong><\/h2>\n<p>result = arr * 2 + 3<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u5904\u7406\u5927\u89c4\u6a21\u6570\u503c\u6570\u636e<\/h3>\n<\/p>\n<p><p><strong>NumPy\u975e\u5e38\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u7684\u6570\u503c\u6570\u636e<\/strong>\uff0c\u7279\u522b\u662f\u5f53\u6570\u636e\u53ef\u4ee5\u52a0\u8f7d\u5230\u5185\u5b58\u4e2d\u65f6\u3002\u4e0ePandas\u76f8\u6bd4\uff0cNumPy\u7684\u64cd\u4f5c\u901f\u5ea6\u66f4\u5feb\uff0c\u4f46\u5176\u6570\u636e\u7ed3\u6784\u548c\u64cd\u4f5c\u63a5\u53e3\u76f8\u5bf9\u8f83\u4f4e\u7ea7\uff0c\u56e0\u6b64\u5728\u8fdb\u884c\u6570\u636e\u5206\u6790\u65f6\u53ef\u80fd\u9700\u8981\u66f4\u591a\u7684\u624b\u52a8\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001PySpark\u8fdb\u884c\u5206\u5e03\u5f0f\u8ba1\u7b97<\/p>\n<\/p>\n<p><p>PySpark\u662fApache Spark\u7684Python\u63a5\u53e3\uff0c\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u80fd\u529b\u3002Spark\u662f\u4e00\u4e2a\u5206\u5e03\u5f0f\u6570\u636e\u5904\u7406\u6846\u67b6\uff0c\u80fd\u591f\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u5e76\u652f\u6301\u591a\u79cd\u6570\u636e\u6e90\uff08\u5982HDFS\u3001S3\u3001Cassandra\u7b49\uff09\u3002<\/p>\n<\/p>\n<p><h3>1\u3001Spark DataFrame<\/h3>\n<\/p>\n<p><p>Spark DataFrame\u7c7b\u4f3c\u4e8ePandas DataFrame\uff0c\u4f46\u5b83\u53ef\u4ee5\u5904\u7406\u5206\u5e03\u5f0f\u6570\u636e\u96c6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from pyspark.sql import SparkSession<\/p>\n<h2><strong>\u521b\u5efaSpark\u4f1a\u8bdd<\/strong><\/h2>\n<p>spark = SparkSession.builder.appName(&quot;example&quot;).getOrCreate()<\/p>\n<h2><strong>\u52a0\u8f7dCSV\u6587\u4ef6<\/strong><\/h2>\n<p>df = spark.read.csv(&#39;large_data.csv&#39;, header=True, inferSchema=True)<\/p>\n<h2><strong>\u6570\u636e\u7b5b\u9009<\/strong><\/h2>\n<p>filtered_df = df.filter(df[&#39;column_name&#39;] &gt; threshold)<\/p>\n<h2><strong>\u6570\u636e\u805a\u5408<\/strong><\/h2>\n<p>grouped_df = df.groupBy(&#39;group_column&#39;).sum()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u4f18\u52bf\u4e0e\u5c40\u9650<\/h3>\n<\/p>\n<p><p><strong>PySpark\u7684\u4e3b\u8981\u4f18\u52bf\u5728\u4e8e\u5176\u5206\u5e03\u5f0f\u8ba1\u7b97\u80fd\u529b<\/strong>\uff0c\u5b83\u53ef\u4ee5\u5904\u7406\u975e\u5e38\u5927\u89c4\u6a21\u7684\u6570\u636e\u96c6\uff0c\u5e76\u4e14\u80fd\u591f\u5229\u7528\u96c6\u7fa4\u8d44\u6e90\u8fdb\u884c\u52a0\u901f\u3002\u7136\u800c\uff0cSpark\u7684\u8bbe\u7f6e\u548c\u7ef4\u62a4\u76f8\u5bf9\u590d\u6742\uff0c\u5bf9\u4e8e\u5c0f\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u5176\u5f00\u9500\u53ef\u80fd\u4e0d\u503c\u5f97\u3002\u56e0\u6b64\uff0cPySpark\u66f4\u9002\u5408\u5904\u7406\u8d85\u51fa\u5355\u673a\u80fd\u529b\u7684\u5927\u89c4\u6a21\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p>\u4e94\u3001\u57fa\u4e8eHDF5\u683c\u5f0f\u5b58\u50a8\u6570\u636e<\/p>\n<\/p>\n<p><p>HDF5\u662f\u4e00\u79cd\u7528\u4e8e\u5b58\u50a8\u548c\u7ec4\u7ec7\u5927\u89c4\u6a21\u6570\u636e\u7684\u6587\u4ef6\u683c\u5f0f\uff0c\u5b83\u652f\u6301\u9ad8\u6548\u7684\u8bfb\u5199\u64cd\u4f5c\u548c\u6570\u636e\u538b\u7f29\u3002Python\u4e2d\u53ef\u4ee5\u4f7f\u7528h5py\u5e93\u6765\u64cd\u4f5cHDF5\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><h3>1\u3001HDF5\u6587\u4ef6<\/h3>\n<\/p>\n<p><p>HDF5\u6587\u4ef6\u53ef\u4ee5\u5b58\u50a8\u591a\u7ef4\u6570\u7ec4\u548c\u5143\u6570\u636e\uff0c\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u7684\u6570\u503c\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import h5py<\/p>\n<h2><strong>\u521b\u5efaHDF5\u6587\u4ef6<\/strong><\/h2>\n<p>with h5py.File(&#39;data.h5&#39;, &#39;w&#39;) as f:<\/p>\n<p>    # \u521b\u5efa\u6570\u636e\u96c6<\/p>\n<p>    dset = f.create_dataset(&#39;dataset&#39;, data=np.random.rand(1000000))<\/p>\n<h2><strong>\u8bfb\u53d6HDF5\u6587\u4ef6<\/strong><\/h2>\n<p>with h5py.File(&#39;data.h5&#39;, &#39;r&#39;) as f:<\/p>\n<p>    data = f[&#39;dataset&#39;][:]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u4f18\u52bf\u4e0e\u5c40\u9650<\/h3>\n<\/p>\n<p><p><strong>HDF5\u7684\u4e3b\u8981\u4f18\u52bf\u5728\u4e8e\u5176\u9ad8\u6548\u7684\u8bfb\u5199\u64cd\u4f5c\u548c\u6570\u636e\u538b\u7f29\u80fd\u529b<\/strong>\uff0c\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u7684\u6570\u503c\u6570\u636e\u3002\u7136\u800c\uff0cHDF5\u6587\u4ef6\u7684\u64cd\u4f5c\u63a5\u53e3\u8f83\u4e3a\u4f4e\u7ea7\uff0c\u9002\u5408\u9700\u8981\u9ad8\u6548\u5b58\u50a8\u548c\u8bfb\u53d6\u5927\u89c4\u6a21\u6570\u636e\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n<p><p>\u516d\u3001\u5e76\u884c\u8ba1\u7b97\u548c\u5206\u5e03\u5f0f\u8ba1\u7b97<\/p>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\uff0c\u5e76\u884c\u8ba1\u7b97\u548c\u5206\u5e03\u5f0f\u8ba1\u7b97\u662f\u975e\u5e38\u91cd\u8981\u7684\u6280\u672f\u3002\u5e76\u884c\u8ba1\u7b97\u5229\u7528\u591a\u6838CPU\u6765\u52a0\u901f\u6570\u636e\u5904\u7406\uff0c\u800c\u5206\u5e03\u5f0f\u8ba1\u7b97\u5219\u5229\u7528\u591a\u53f0\u8ba1\u7b97\u673a\u6765\u5904\u7406\u8d85\u51fa\u5355\u673a\u80fd\u529b\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>1\u3001\u5e76\u884c\u8ba1\u7b97<\/h3>\n<\/p>\n<p><p>Python\u4e2d\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u5b9e\u73b0\u5e76\u884c\u8ba1\u7b97\uff0c\u5982multiprocessing\u3001joblib\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528multiprocessing\u7684\u7b80\u5355\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from multiprocessing import Pool<\/p>\n<p>def process_data(chunk):<\/p>\n<p>    # \u6570\u636e\u5904\u7406\u903b\u8f91<\/p>\n<p>    return result<\/p>\n<h2><strong>\u6570\u636e\u5206\u5272<\/strong><\/h2>\n<p>data_chunks = [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]<\/p>\n<h2><strong>\u5e76\u884c\u8ba1\u7b97<\/strong><\/h2>\n<p>with Pool(processes=4) as pool:<\/p>\n<p>    results = pool.map(process_data, data_chunks)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u5206\u5e03\u5f0f\u8ba1\u7b97<\/h3>\n<\/p>\n<p><p>\u5206\u5e03\u5f0f\u8ba1\u7b97\u53ef\u4ee5\u4f7f\u7528Dask\u548cPySpark\u7b49\u5e93\u6765\u5b9e\u73b0\u3002Dask\u53ef\u4ee5\u5c06\u4efb\u52a1\u5206\u5272\u6210\u591a\u4e2a\u5b50\u4efb\u52a1\uff0c\u5e76\u5728\u96c6\u7fa4\u4e2d\u5e76\u884c\u6267\u884c\uff0c\u800cPySpark\u5219\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5206\u5e03\u5f0f\u6570\u636e\u5904\u7406\u80fd\u529b\u3002<\/p>\n<\/p>\n<p><p>\u4e03\u3001\u4f18\u5316\u6570\u636e\u5904\u7406\u6d41\u7a0b<\/p>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\uff0c\u4f18\u5316\u6570\u636e\u5904\u7406\u6d41\u7a0b\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u4f18\u5316\u7b56\u7565\uff1a<\/p>\n<\/p>\n<p><h3>1\u3001\u6570\u636e\u5206\u5757<\/h3>\n<\/p>\n<p><p>\u5c06\u5927\u89c4\u6a21\u6570\u636e\u5206\u5272\u6210\u66f4\u5c0f\u7684\u5206\u5757\uff0c\u53ef\u4ee5\u6709\u6548\u51cf\u5c11\u5185\u5b58\u5360\u7528\uff0c\u5e76\u52a0\u901f\u5904\u7406\u901f\u5ea6\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7684<code>read_csv<\/code>\u51fd\u6570\u52a0\u8f7d\u5927\u6587\u4ef6\u65f6\uff0c\u6307\u5b9a<code>chunksize<\/code>\u53c2\u6570\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">for chunk in pd.read_csv(&#39;large_data.csv&#39;, chunksize=100000):<\/p>\n<p>    # \u6570\u636e\u5904\u7406\u903b\u8f91<\/p>\n<p>    process(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>2\u3001\u6570\u636e\u538b\u7f29<\/h3>\n<\/p>\n<p><p>\u4f7f\u7528\u538b\u7f29\u683c\u5f0f\u5b58\u50a8\u6570\u636e\uff0c\u53ef\u4ee5\u6709\u6548\u51cf\u5c11\u78c1\u76d8\u7a7a\u95f4\u5360\u7528\uff0c\u5e76\u52a0\u901f\u8bfb\u5199\u901f\u5ea6\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7684<code>to_parquet<\/code>\u51fd\u6570\u5c06\u6570\u636e\u5b58\u50a8\u4e3aParquet\u683c\u5f0f\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df.to_parquet(&#39;data.parquet&#39;, compression=&#39;gzip&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>3\u3001\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f<\/h3>\n<\/p>\n<p><p>\u4e0d\u540c\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\u5728\u8bfb\u5199\u901f\u5ea6\u3001\u538b\u7f29\u6548\u679c\u7b49\u65b9\u9762\u5b58\u5728\u5dee\u5f02\u3002\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u6570\u636e\u5904\u7406\u6548\u7387\u3002\u4f8b\u5982\uff0cParquet\u548cORC\u683c\u5f0f\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\uff0c\u901a\u5e38\u6bd4CSV\u683c\u5f0f\u66f4\u9ad8\u6548\u3002<\/p>\n<\/p>\n<p><p>\u516b\u3001\u603b\u7ed3<\/p>\n<\/p>\n<p><p>Python\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u65b9\u5f0f\u591a\u79cd\u591a\u6837\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u6570\u636e\u89c4\u6a21\u3001\u8ba1\u7b97\u8d44\u6e90\u548c\u5177\u4f53\u9700\u6c42\u3002<strong>Pandas\u9002\u5408\u5904\u7406\u4e2d\u5c0f\u89c4\u6a21\u6570\u636e\uff0cDask\u53ef\u4ee5\u6269\u5c55Pandas\u7684\u529f\u80fd\u5904\u7406\u66f4\u5927\u89c4\u6a21\u7684\u6570\u636e\uff0cNumPy\u9002\u5408\u9ad8\u6548\u6570\u503c\u8ba1\u7b97\uff0cPySpark\u5219\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u80fd\u529b\uff0cHDF5\u683c\u5f0f\u9002\u5408\u9ad8\u6548\u5b58\u50a8\u548c\u8bfb\u53d6\u5927\u89c4\u6a21\u6570\u503c\u6570\u636e\u3002<\/strong> \u901a\u8fc7\u5408\u7406\u9009\u62e9\u548c\u4f18\u5316\u6570\u636e\u5904\u7406\u65b9\u6cd5\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u6570\u636e\u5904\u7406\u6548\u7387\uff0c\u6ee1\u8db3\u4e0d\u540c\u573a\u666f\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\u63d0\u5347\u6027\u80fd\uff1f<\/strong><br \/>\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\uff0c\u6027\u80fd\u662f\u4e00\u4e2a\u5173\u952e\u56e0\u7d20\u3002\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\uff0c\u5982NumPy\u6570\u7ec4\u6216Pandas DataFrame\uff0c\u6765\u63d0\u5347\u5904\u7406\u901f\u5ea6\u3002\u6b64\u5916\uff0c\u5229\u7528\u591a\u7ebf\u7a0b\u6216\u591a\u8fdb\u7a0b\u5e76\u884c\u8ba1\u7b97\u53ef\u4ee5\u5145\u5206\u5229\u7528\u591a\u6838CPU\u7684\u4f18\u52bf\u3002\u6b64\u5916\uff0c\u8003\u8651\u4f7f\u7528Dask\u6216Vaex\u7b49\u5e93\uff0c\u8fd9\u4e9b\u5e93\u4e13\u95e8\u8bbe\u8ba1\u7528\u4e8e\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u80fd\u591f\u5b9e\u73b0\u61d2\u52a0\u8f7d\u548c\u5206\u5e03\u5f0f\u8ba1\u7b97\u3002<\/p>\n<p><strong>Python\u4e2d\u6709\u54ea\u4e9b\u5e93\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\uff1f<\/strong><br \/>\u6709\u8bb8\u591aPython\u5e93\u53ef\u4ee5\u6709\u6548\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002Pandas\u662f\u6700\u5e38\u7528\u7684\u5e93\uff0c\u9002\u5408\u6570\u636e\u6e05\u6d17\u548c\u5206\u6790\u3002NumPy\u4e13\u6ce8\u4e8e\u9ad8\u6027\u80fd\u7684\u6570\u503c\u8ba1\u7b97\uff0c\u800cDask\u548cVaex\u5219\u53ef\u4ee5\u5904\u7406\u8d85\u51fa\u5185\u5b58\u9650\u5236\u7684\u6570\u636e\u96c6\u3002\u6b64\u5916\uff0cPySpark\u662f\u4e00\u4e2a\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u7279\u522b\u9002\u5408\u5728\u5206\u5e03\u5f0f\u73af\u5883\u4e2d\u8fd0\u884c\u3002<\/p>\n<p><strong>\u5982\u4f55\u4f18\u5316Python\u4ee3\u7801\u4ee5\u63d0\u9ad8\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u7684\u6548\u7387\uff1f<\/strong><br \/>\u4f18\u5316Python\u4ee3\u7801\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\u3002\u9996\u5148\uff0c\u907f\u514d\u4f7f\u7528\u4f4e\u6548\u7684\u5faa\u73af\uff0c\u5c3d\u91cf\u5229\u7528\u5411\u91cf\u5316\u64cd\u4f5c\u3002\u5176\u6b21\uff0c\u4f7f\u7528\u751f\u6210\u5668\u800c\u4e0d\u662f\u5217\u8868\u6765\u8282\u7701\u5185\u5b58\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u5927\u91cf\u6570\u636e\u65f6\u3002\u6b64\u5916\uff0c\u4f7f\u7528Cython\u6216Numba\u7b49\u5de5\u5177\u5c06\u5173\u952e\u4ee3\u7801\u52a0\u901f\u4e5f\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002\u6700\u540e\uff0c\u5b9a\u671f\u8fdb\u884c<a href=\"https:\/\/docs.pingcode.com\/code-review\" target=\"_blank\">\u4ee3\u7801\u5ba1\u67e5<\/a>\u548c\u6027\u80fd\u5206\u6790\uff0c\u4ee5\u8bc6\u522b\u5e76\u6539\u8fdb\u74f6\u9888\u90e8\u5206\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u65b9\u5f0f\u5305\u62ec\uff1a\u4f7f\u7528Pandas\u5e93\u5904\u7406\u6570\u636e\u3001\u5229\u7528Dask\u5e93\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u3001\u91c7\u7528NumPy\u8fdb [&hellip;]","protected":false},"author":3,"featured_media":1043288,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1043279"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1043279"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1043279\/revisions"}],"predecessor-version":[{"id":1043290,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1043279\/revisions\/1043290"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1043288"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1043279"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1043279"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1043279"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}