C# 多线程的代价~内存都被吃了!
异步操作是.net4.5推出的新名词,事实上,这东西早就有了,它归根结底是通过线程池来实现的,即将一个大任务分成多个小任何块,每个线程并行处理其中的一个,完成后再把结果告诉主线程,在.net4.5推出后,这种技术得到了封装,让开发人员实现起来更加方便了,但是,并发(导步,多线程)并不是在哪里都适用的,使用不当,可能出现很多严重的后果!
看我的程序,这家伙已经占到了2.6G的内存空间了,很可怕吧!
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j2+JWqb7EjD4Vv44wAsCWpE6sH8Z9ZdtiMYPylZ2fH8XKKadQsspY4Ti525O2xWykjAGxJts+ejNXWWvQx8iMQj/+CRl7V0esZ+Vg7cvnhmPrxSPa5ivoxi/VRjJ/LalJ2rBbulwMAzahGrs56mUvdmTFhdySy6haPi+W0LctyXBWtJJhxoB25jLuchDMP/OqCtatji6UBYCXkDbScidZLjPxQRCJveWRVD6ojJFh1ZFxVHYy1I5+MX5D4/Rf07+L9u9UYfwBZN2gAsBSWkavJZC75LrN1F4Jht5JV7ZoOZeTTUDtyNXDFG7GqjXjDPZ08w4oAsCXxm3WZCyM/CPGY+8ZZezdQ1dfsyJf5aD3yEUqaRh6nafySZRanSWliq3D1ogBgDtkcnJ5P52zKy6XDn6rq8lI8Aw1YvWYls86o5TiFVC3OxTFjlWwNyHs5I+7IAQDg9AxykzTWjhwAAAZhEBe/wY4cAACgV9iRAwAA9A07cgAAgF5hRw4AANA37MgBAAB6hR05AABA3wy0Iy9+zd/P4j/nIV5OVa5Je4aAU0VVqxah+IAFgE5pGMYM+81Q15ngOqk+aEV9KkuxkGZDachiedBAO/JmG057N55rkXKqjLyq5DlYkZTtZFGDXrDGKmP4mKjrTNEg/fVKlhYpqnY9r80VrGuUHXnzhIz7aKScqqKOZuR+ezBy6BeMvF/ia06VkUcqbfPjWop1DbQjn9xnmGcHaUr1Mw31ZSRZ1hlqRU4uNY1VuHP5wTZbhThXkZ50ygE4DsE5lZ65PCdNsGXLB0ftNT99dmx1YtVy2txgOaL8Jjm1j7IjT0Mgj+VBlsYfLs54KpYcOQi22RlYbSWr5VgjWC0KoAvi8zduFbANVSuP49POkmhV2tbdi3vQWDtyK3a+KxdNywq9vKvym+EcLGLk6m1dMY1ssDWCgysdwAFpuBGPlAMb0LaF2NHIJ3eFn5o8aJQduRWX4v6y2cjjZ7YxcvVMwxxwIhkvBOBQYOR94a9CkYzWAlhl5JEaI22e6UED7cit7aa/K7WypCetXWyxnEl0oUyWjS1ZptVsJwJp3mIDiljRqC0HYF+suVCc6TJLekamKZ6BCGq0I/GP5Ip3dHyhsxZG+VKWb6W5nxllR+4EN554bQ7VGACAruliRZ3fyIF25Gr4DtXN7GIBAJbi+Gvpggv+6DtyAACAfhl6Rw4AAHAC2JEDAAD0CjtyAACAvmFHDgAA0CvsyAEAAPpmoB259X18ABgZ9REc0/NvB1mP6SiemY73TVe4I3ttWvmBMLJSv7pIXQPtyNPrr51UTEKAs6KuDPd100ojf6rZMfKDI/sl6BTq2IhX54yitrpG2ZHPmUhMQoCzos5ux8idvDIXRn5wZhp5w55QZiwWUqxroB35JKaT+pGF/KBD/dxDTcBcBegRdfI6U95Pg5F3hLN6+13W1qfNRq42Lz05yo5cjZq841Zjqt53T89vlNpu0ADgIFjTPJ4mWwRYGfpi2V2yn2tmXdkYG2tHbkWheOtt3Xdj5ABnIrK8OmkcX2dlOD7+dk5NvKORZx8kjLIjtwJnfULCdAUYAWdlqDqehBOwMhwf2ZvBnqpyfT9X0MidSgfakctbGDUiTjL1hmhiugL0jDrlszO1aVgZOqLYj34WJ5mfS609XleWcZQduROmeGIAAIBDMdCOXBK/kwIAADgso+/IAQAA+mXoHTkAAMAJYEcOAADQK+zIAQAA+oYdOQAAwBZc3O8/Z29J5FsTO3IAAIDN8I3c+q558WCgHXnxa/7r4TxkIPuyf23bdrwogHOQTSL/+RvZbC2emfim67Gx1k+ny9Rerq3u8tytZb3+QVrIQDvyNF4NZlmVvracOW2btG4GgCDq7MsWWZlG/lSzY+QHx1p7i13WvOpag0RNILEKHGVHPmciYeQAZ8VZHIszS12Cs4V4wsgPTOQ2zsk4Z0+o3gvKZqgHWZkD7cin0vPS04M0pXorpCYodqpMIDNaafxiZXus6y3Wroao4WIBekEdz86U99MUZyIcELkIR1bdBWu5PDcg+ZZMkyYeZUfuhFI9sLKoYZW9UqzaqjSSxi92Kn1c03Dg1AVwDqwpE09jLc1WaXAQfFNwslR1qzoe/APVs2WZY+3Is4u3OsNxQRlfq3v8etVmROqKFOuf8U1a1qVGg1UJTokzEyNpHF9nyhyW4Eqo5mroVsvI/fao5aTnR9mRW9PP6q01pmubkTsFWmmajXxOFQA94qwMVceTmFwY+fGpWvTUd5u93Mqeliy5n0+zDLQjt26y1O1mcRuahXUqTVfZGU5XOXU5JRfTWxfl5JXtseID0CmRSVeb5oKRd4K16k7agilz+cmsvFMyHoILtdPs25lRduR+WAEAAFYluxFUE6i2bZ25jPw7cidkAAAAi+NvrNXPAyTy3duZ0XfkAAAA/TL0jhwAAOAEsCMHAADoFXbkAAAAfcOOHAAAoFfYkQMAAPQNO3KPqqcEAMCZaJjsLA77Eol/9mVu58tdTgkND4RJHwVT/EK5Van61nA78oZpFvl6fnNRAHAErLnJnO2IiKdmaYrPWnHKiSSTWaSRx3FyjbUjx8gBQIKRn4OGHXlDCVOTH69n5GPtyNUPTOQNmvyYJcvbXE7tDaP16U38wxwAKOLMaHVST88nuJywsBcNRm4t1H5RbX1tDSqnPcGMQ+/IL8/dWiaYEiOP5HLKsU5G2uPXDgAzia8MxfV9hdZBlFojl+fVxTaSON48a7BlL+MHY+3I1bjHb5GqAi3LUWu3GuMMpuANIwDEabjFj5QDGzOmkU/syNXzzdF0ylHf9Zs3VY4tAGgDIz8HtUYuj6uMPFijU4Xzkh259/Uza8N9D7H6MnsrPRMpVq1dHQFq+VbhzmUCQBXFKVycdzKBTBw5A20E419cTqs6umopvmex6rJKtkbjvZyxduQAADAIg9wkjbgjBwCA0zOIi99gRw4AANAr7MgBAAD6hh05AABAr7AjBwAA6Bt25AAAAL3CjhwAAKBv2JF7yC/78yQWgDFh4h8fv48uz8lOxotqeyBM+jQY/6k1TqXqW8PtyBumYlUH1xYFAEeAuXkCip7qL+bygWuRotoe69Y23pxcY+3IMXIAkDA3z8EiRh7x2gY/Xs/Ix9qRqx+hZGfUD16yvM3lRD6EkVmswv1yACCInJvW/HUS+OdhG4ru6/R1VkikqIbm+Yt5cVxZGYfekV+eu7VMMGmd6uRyyrFORtrj1w4AM7FWhkia4PSHDYhH3lpag50YMftgroZxlR2MtSNX4x6/RaoKtCxHrd1qjFqdkwYA5mCtDE6a4KyHLZlv5FNsjT2UkU/syNXzzdF0ylHf9Zs3uaMNAJbCmlb+LbV1AHsR2Uanx5H+9Yuq6nR25MsY+VT6nYT1MnsrPRMpVq1dHQFq+VbhzmUCQBVyOqtn5Etr9ZhKd/bWGWhDLoxqtIPLqbPGWi4QaWHWqsi4muwBeS9nrB05AMBK+BYC2zNIL4y4IwcAWAk+LTsOQ/UCO3IAAIBeYUcOAADQN+zIAQAAeoUdOQAAQN+wIwcAAOgVduQAAAB9w47cg2+SAAxLw/RnudiLy3OKyarOOIXEB0n6NJiGRw44FQ23I2+YZsxMgNPjPMNr45ZAG5GeSh+LVjzwy1TTR2qXRh7HyTXWjhwjBwAJRt47VUYePFM08qrhsZ6Rj7UjVz8wsT5UyW64Lhpq4VWfumQVqbniH90AQAP+jFbPqEsBU3VHrJXZT6PmKpYztfa1VVfxKooZh96RX567tUwwJUYuXzrZI91sZc96y2oYACxFfGUoru8rtA7qsHpBLq2RM05Rtd2t5moYe9nBWDtyNe7xWyTZE34uqw2yZCejdYMGAAvScIsfKQd2YTQjn9iRq+edkPk7cquiSGNkscFyAGAmGHnvRJbNxY3cT2PlYkc+18in0u8krJfyOIumldLqrSxj2jCrhc5FAcBM/JVhCsxEmUAmjpyBNoLxLy6wVR1dtThnxiHrskq2RuO9nLF25CvhDx0AANieQVbjEXfkK8G+GQDgOAy1GrMjBwAA6BV25AAAAH3DjhwAAKBX2JEDAAD0DTtyAACAHXC+ICexsrMjBwAAWJ3sO+L3k9aBzO6cZ0d+aBoeVgAAi9Aw0ZiYOxJZGyMrarEc67EtkRZGDvwduTw/3I78+NPsYjxbJruPm3q4FoBeqN0GwdEo7min2IoaKSeezMnl+HS8xvvxWDvyI0/LdBjJdmLkAOuBkfdOpKeqjDxSVO3wCDbS35HLAsfakasfUKQH2fksixVKK5dfcqSFTi7WF4ClcOadnL/p1LaWFNge3/DuabJj9UyxnKmpr53xY5VmnZQZh96Rq7O3eOAUmx3IUVIsJ9KjLBYAy7LIOlB8F9YjuEJat1+pxQbL8RMUGxk5ExxsY+3IZVz8+500TeTuLPNg9abB8umsIqd3WSkAFidu5FXlwGbUbnWsNXYbI5e7av8taRzZy9F35E6g05PBO6PsTO3YcrK0jRsAiICR906VATsHzeVUNVJu29QV3m/A3ZiG25FPiStb+2P1FqkY3DSLPJBpgvg3a/FyAMDHmq1y9vkl+E4QOQNtBONfXJarOrpqKU5zqT+z8iOr/aXey89g5A0w0wAAuuNQS3d2U6j+lFkiBY64I6+CjS8AQI8ceenO2pbt7x0m4wMDduQAAAC9wo4cAACgb9iRAwAA9Ao7cgAAgL5hRw4AANAr7MgBAAD6ZpQdefDL9dOMLy00PBkgyyJPBh8IELmuNbDqXa8lDSUvGJ8jf6Flanq0BUxihMgDK03kzMS3WFdARnuKjfb4HHHKUXu5rc1WykiBdwbakd+D3hCmOFUlp+Mvy2ud8WvcZbFornSb1u4en1Wxri4+fkCNUhZAK7ZWMox8bayYy2M111SaI3Gvjffsqh40yo48DeV6LGXk8dJ2XyA6MvIz4S8KGHkcNTKOkTt5ZS6MfG3WMPKI1zb78RojYaAduRpE+UFHNuWsT0KsjDPv6ayKnEKsNOpFZQdylfFz+VfhtCcSLrV2P6TB3lkqPk45TiNVInEullOMYXrSb8/gRIIWT1PsWVgKP/5++nvXyHflW2pRbX3qL1ayZJlAPT/0jlztCSvNzAOnomKrIiPGGZGTYa6Rg2LVVTGMpPFj2JbLKqQqPnNqj+TyW6iWY3WQ02awmDNo05dqt9ILa2CNcyvaMo1zxu+y5m5dY20cfUc+uSu4FTuZy0nTYOTBM36BWe1WgWqDg0PZSdMWZ6v2KitV65KJG+JTfKmWrDZDpilGw2meM1oiPQh3nB6JpFFfWn0E87H6It53aq7gLHYqCrY5rc5JE1nlht6Rq+eLQYysm5GVNEsTHGSRljstzE76VUSGabABTuJi7XN6Z8H4VLXZwcoV6W6nKH/8gEXEDIKGoc5o+mI9VjJyv5Ds3dqeXcODxtqRy5sseeflvMwO4kWpM7mY3qnIL8dquRxA6hk/l1O7k9FvZLF2q2Q/jfpyTnyK5ahnZLF+y/3qfKz41JYzFGqInEhG0tw7NPsJyxKZjDJLcKI5s0adv8EGW7XLgeTUJXONtSNfBH+gwL7QOwBw46wrQLbKjbUjXzaOVTdisCX0DgCcewVgRw4AAHAS2JEDAAD0zfl35A8/+eJ///wVP/nJT37yk5/n+znEjvx2tQghhND5NMqOHCGEEDql2JEjhBBCHWugHXn2pwF+UJqjGc+rNsZvdlVRmw0gtd71WtJQ8oLxWeS6Gtozp/Hbj4rulPWIPLDSRM7M7L4RFJkOWRoZ7WA5D8aMmLR1ONKYeOeqbY630NFAO/J70BvCVDUiGxLLVllniuNvpetacMxt3Nrd47NUe+KLxS5x7ldqj2QT0JqbVrJsiY+v9QOqapVTeyRejtUX2d1AsJxiGjXLGh7U4N/9GbnV2WsPynhiq2sjpe2+QHRk5EfQ2uHyFykUDKxj5E5emQsjr4p/MM7FM360i70WKafZj9cYCQPtyK0uzMJe508AABFvSURBVPw+m3LODYGaUeaN9KhVe6QQK416UdmBXGX8XMFx2RYutXY/pMHeWSo+TjlOIxv6Sy1ZNswJSNY7TlStGPrNtmISKeeAsnqkLU0xSsjqBb+DguM2MpLly2yiBZs0/zKtS3MSyPPT4DtytSesNDMPnIqKrYqMGHX8WYMj3vjaWbFqnJtzLRKfObU39Jd64OeyWlhbl9Pa2vZ0pDmDVo1J+rLTmOwVfOddf3lcZKmMlNbcrWusjaPvyB/cFdzv4MiS6huhs/BFzvgFZrVbBaoNrlqRIwMxGGerdmdqRXpnqfgUX6olB/srMiTkqFNP1kY10t1tdXUn5+oiadSX6kBCTtxq+6VqvZLJsnEbGQMPM7rVmtp+C9U4pOeH3pFHBkpwkY0ntnLJNjQvK04LnQEUzNXWgHici8O3qncWjE9Vm9vC1TbGIi2sOigWez8TXPWOLOsSao9lJOVP5Mc/3kf+mYYaI6tNMf2c652zyo21I5fWniZT06Qvs4N4Ueo4K6Z3KvLLsVo+iQGknvFzObU7Gf1GFmu3SvbTqC/nxKdYjjWE4v0VaaEVAVmUTBlpsDow/Gj7ITq41B6RnViV5h6c7Cfy4z8Zs0ZGOxL/YDnpeT+NWkjVgHeuwqpdrUuOtLF25EuNPPUYHUH0Tjw+RAkdU0uNybOO7WyVG2tHvmwcV7pLQPNF78QjQ6zQ0YSLB6+OHTlCCCF0Bg20I+cnP/nJT37y83w/qyzyZsn9GTkAAMBZudllhLslTxg5AADAQYjbJUYOAABwODByAACAjsHIp8vlslkaADggl4T7y/TAShM5k5UDu6P2RXoy7USrhIbOvaeX1QWzWykx8hVh6gIcH3VJzVZbmUZdlGV2jPxoqH2R3bGl551yimnULNLI42DkO8DUBTg+zv6suFhn52UujPyAFHvNSunkiteLkc8ycusOWv1ERZ6sSpMmK3ZMcdqzCgCsirVLa0uDkR8c38in2Ord1qdt/lLMOLqRT0anzk+jnrESZAdqsSwEAKtiTfN4mmz+WmsO7Iu/wPqrevZWbbequYr+UjwYyMgn4z5rXyNX77OKaQBgDSKLeGRlSF9i5EfDX2Mx8g6MvCGIbWnUM8UEVSMJAOZjTbfa40msDBj5MfE/a6kycj+NlQsjX9jIs81udl+WHlSlycpXe6tYmtVIAFiQS4I82ZYmXWrksgM7Elyr/SVXXbeDtU/1HjRpIzA9HsvIAQAATgZGDgAA0DEYOQAAQMdg5AAAAB2DkQMAAHQMRg4AANAxGDkAAEDHYOQAAAAdg5EXHtTAw1gATo98kEvxiRzq418i5cDuqM9jsZ7KYpXQ0LkX4wFB8exWSow8BJMQ4KyoS2q22so06qIss2PkRyPrC9kvaqer5USSySzSyONg5LNgEgKcFXV2O0bu5JW5MPIDEjTySCFV3YqRL2Dk1h209TGLHz41jfr5jF+y2s7iQsC6ALAg6oRSJ3gkDUZ+cPw1P7hWt/WpLDnuQU7G0Y180qaiPF9M03ZgNVIeqI1haQBYEGuax9Nks9Vac2BfrL4ouoOfOF51ZBRVHQxk5JPxJwyLGPm98KrOcFro1x65YQSAWiKLeGRlSF9i5EcDI+/eyBuCWBXoqs6wWui3mRUBYEGsyVV7PIk5jpEfE783q4zcT2PlwsgXNvJsa5u+vGhkGWU5VhpZsuw/P6XTbABoxpm8cv4G06QT3JnssD3FflTPOIVULcVyMFijaDIcJDtzOx7LyNcj65iNawcAgGHByBeDXTIAAGwPRg4AANAxGDkAAEDHYOQAAAAdg5EDAAB0DEYOAADQMRg5AABAx2Dkha9986UygNMjH+RSfCKH+viXSDmwL3JJj5xxCol37iV5GkzDo0ecijDyEExCgLOiLqnZaivTqIuyzI6RHwqrp9Jj9a1IUcHapZHHwchnwSQEOCvq7A6u6dl5mQsjPxSyFxwjjxRV1a0Y+QJGbt1Bq5+oqPMzOyPTZHnlcWQ+qyWo7fTLAYAg6oRSJ3gkDUZ+WNRVOn1XTeMU1dwAqxzHg5yMoxv5pE1Feb6Ypu3AaqQ8UBvD0gCwINY0j6fJZqu15sBeWAtpapPOyi+Lqu1WNdd8fxnIyCftpiYSxHga326DRq7eeRXTAMB8Iot4ZGVIX2Lkx8HvX4y8GyNvCGJVoKs6w2qh32ZWBIAFsSZX7fEk5jhGfjQie60qI/fTWLnWMPLXX74O6oRGnm1t05cXjSyjLMdKI0uW/eendJoNAM04k1fO32CadII7kx22p9iP6hmnkKqlWA4GaxRNhoNkZ27HT6+eqtS3ka9H1jEb1w4AAMNyt8vanxh5DrtkAADYhVr/njByAACAg8COHAAAoG/YkQMAAPQKO3IAAIC+YUcOAADQK1UWydfPAAAAjsXNLiOc4YEwKv4XxvhSGcDpkQ9yKT6RQ338S6Qc2BHZR9OGD4S5JE+DaXj0iFNR3C5Pa+TBCC5bIAAcBHVJzVZbmUZdlGV2jPxQWD2VHgctVi0hUrusJQ5GPgsmIcBZUWe3Y+ROXpkLIz8mSxl5Vbdi5AsYuXUHrX6ios7P7IxMo35i45estrO4ELAuACyIOqHUCR5Jg5EfHMuqa428oU+lC8Q9yMk4upFP2lSU54tp2g6sRsoDtTEsDQALYk3zeJpstlprDuzLUkbuJ4jnmu8vqV1eNM5j5JN2UxMJYjyNb7dBI1fvvIppAGA+kUU8sjKkLzHyo3FuI5defqodeXMQqwJd1RlWC/02syIALIi/rMePJzHHMfJjsqCR+2msXGsbeerlliVPZzLybGubvrxoZBllOVYaWbLsPz+l02wAaMaZvHL+BtOkE9yZ7LALF2GctQusukrHq46MoslwkOzM7Vi1y4tw8ZMY+XpkHbNx7QAAMCxxu8TIC7BLBgCA7cHIAQAAOgYjBwAA6BiMHAAAoGNuxhcURg4AAHAsnl49VakbI6/KUpseIYTQaEotcO2fta2qVTdGHryXqU0PAACjcf+sdxsXr2rVyY18jfQIIYRGU+YUmzl6sFW1wsgRQgiNpe135PFWNVxO30Yun1qHkSOEEPK1745cfd7qdUwjvz15LZ4eIYQQuu69I1fN6zqgkd8foRpMjxBCCN20+47c969adWnk6b+OiaRHCCGE7jrCjlxa2FhGfmVHjhBCqFXsyJ23+B05Qgiho+sIO3KrVQ2X07GRX/mrdYQQQvXafUfut6pWfRv5/PQIIYRGE98jd97CyBFCCB1dPNnNeQsjRwghdHSxI3feWtHIa/8/azw9Qgih0bTljry2Vec0coQQQmhZbePita06p5E35EIIIYQG0dGNfAIAAACXQxs5QgghhJYSRo4QQgh1LIwcIYQQ6lgYOUIIIdSxMHKEEEKoY2HkCCGEUMfCyBFCCG2nPb7J1R9Vj5HZx8gjj7VrLrxK2f+eU/+nrPX/6eZX57fESXA/Vgu8nbw8Z4NgIoRQUdus7V2r9sGuuxl58YF2auEXm2IyNYH6UlZqXUiwPcXSgncP0r8zd88uqngJDZeMEEJzhJEX1ZORO58qWIUvZTyR7a+PzOgYp1+OVbJ1T+DfNMSN3K8LL0cIrSGMvKjujfxyufhG7jtrUJb5FVM67/pG7mSXGas82HnLvxtobjZCCDWrzTiqVid/yc2OnTV2jsvMUd9GfgvWnB254/RpT2RnrN7yC/GrizdbFuiMJ3m9amOKXaCWEIw2Qgg1aw0j9xZ9sWhbB1d7pZU1Np+PqDMjv1wumYtfFt2RF89nVup7qt+1TpdXGbl1UHxXvuXEp/ZKEUJoETUYh7WsNa9dfiFxI7+v4WpRzUtof0Z+c+57CPzfkQeDW3y3aORq9/j95Bu5U5Rf+EU4rtOk+EiS5yNnEEJopmqNQ67PV2O9Kq7YxWLlW045anvk4t8Qoi6N/I7/x25+d/onZXDTvqnqgypn9fsyq109brguJ0H80py8CCHUrAYjjyyq/kIqy7G8w7d/v0a/VXF1ZuRyLx75q/Vi+Hx3lwkifq92cOS42JdORr/ZfiicG4tIiIrNRgihBs38HflSq7Gz26ldRdOUTpq4+jPy7DflxY/WZec59hMx+Mj5SPnBYRQv0Ho3nt6v/V6aOgRxcYTQGprzO3I/jUVVMv8WwWqVXJzjLZfq0sglfuERq/ZfBk13MyO3xpxsc9VtQTF9ZIAihNCCav5oXe49rCXaeuu62i8ol11LuzHyYhr1d+Q+avqq6BddMC0zMoYivejcAajl+NeujnV/WEeSIYTQImo2jpt8+0w92F//rdU1e8u3GKdYq4UR9WHkzl4825cjhBA6k5p/Ry7t2XJNZytVLMQpVm3V1fb75n1RH0aOEEJoTLV9tJ69zFzTcdAs2TXgr1W7aufDzuYQYeQIIYSOq1U/WnfOO3cD6n2AnyYrOZIsLowcIYTQcYVxFIWRI4QQOq4wjqIwcoQQQscVxlEURo4QQui4mqbp9ZevkS+MHCGE0EH19OoJRRQPKUaOEEIIdSyMHCGEEOpYGDlCCCHUsTByhBBCqGNh5AghhFDHwsgRQgihjoWRI4QQQh0LI0cIIYQ6FkaOEEIIdSyMHCGEEOpYGDlCCCHUsTByhBBCqGNh5AghhFDHwsgRQgihjjXXyHf/p60IIYTQ4Go38t3/XStCCCGEnpqNHCGEEEKHFUaOEEIIdSyMHCGEEOpYGDlCCCHUsTByhBBCqGNh5AghhFDHwsgRQgihjqUY+e7fee9UBPAgoiMQSsWMOKvSnlWMfPf7ix5FAA8iOgKhVMyIswojXzemuzdmZNERCKViRpxVISO/XC73DPfj9GT27uU5ahqnkN619mxZNoCn7AKnI/wBnEVG0hDAE0cY9SWM/KyK7sjl8pfZSbrMWU5zt/ns58m0r5Gr9pP1js/uAVy1I4p3ovcg+GPe6YLaBAhtI4z8rKr7aN1f9ItGHnk3Iln7oUxI/UgjcwjVXOWxeu1qRxSD32ZCkV5Qaz9CX2QdIe05eAnqgUUxgd+/TpydvjtU2NFhhZGfUtM0Vf+O3FkyrFVMPXkxLK2oyDq7e1jTAPoLbu1VZO8G13f12D8T7wi1kCP0hewIOfxkg30zjgc50ptVQc6Os8YcJ+zosMLIz6fbvxe/vzSN3FrC5LIS8eNiUfKlLKF4ZvfIZgF0rqLKyNUbINlBFrKo9K3awFrpI8Ngx46Q1pidrzpwjrP0TkcEg5zVLl8eJOzosMLIT6abi4eM/KaI3xSXLbniWBbiyLeu3SMrA6i2ygqOE41a13GO1V6rld/Fu/eC7AgrJtnP+xXFHd3qO2eONMTZCfKhwo4OK4z8TJIufo0YuUWWIM2SVqCufW1Gnh1H7Grj+KYBtIzcOuNfQuY3akc4sVJDN98GjmkqzkiWAVdNuhhkq5C0IqfT5wTW6VCEVGHkp1Hq4unDWOfuyK31MdP81Qcj9xOr9pOZino3MCd6qoHt3heRXxIVB7ZzpuiyapylwccDK7v4gGFHhxVGfg5lLr7YR+tyFZNrjXXyWrn0OPXWFrVelNMAWmuxdV3+JRRDZ0XDKnYp85at2r0vnJHsjGdrxMpxWwym/7I5yNZbBwk7Oqww8hNIuni1kfvGUFy2nJsAP6NMoG5HDrKEOV8/81sbuYSiNxeNXPUn6VXNHRHMu0tHxONjhdS/ugYjbwiybOehwo4OK4y8d/kufo082a3KY6z06rp/stVn1dmSLdm+60Rc+WTBL3aE5XlWPNUQLWjkCG0mjLxrWS4e+h15ZgbFDZyVRm4gqjZ/HWkDI5cO4dwSWVu680U+0hHq2LP2u9Zod9JbsXW6AKFthJH3K8fFKz5aR1URJ4BHEB2BUCpmRKfyXRwjXyvoBPAIoiMQSsWM6FFxF7+qRj5BKwTwINARACnMiB6Ju75i5AghhBDqRRg5Qggh1LH+ZuS3j90RQggh1JeeXj1dnl49IYQQQqhT/R+alCnE3KIqRgAAAABJRU5ErkJggg==" alt="" />
出现这种问题的原因就是我没有把线程这东西搞清楚,在一个调用密集的环境里,使用了多线程,要知道,这种线程,线程池里会有N多个线程的,处理的速度我没有觉得提升,反而内存吃的很严重,这个原因就是因为你的工作线程太多的缘故。
所以,多线程,并行,异步这些东西不是在哪都适用的,在调用密集时就能用它,因为它会吃你很多内存,如果非要用,请你把线程池的最大数限制一下,这个值可以控制在10以内。
下面是多线程吃内存的例子
while (true)
{
// ThreadPool.SetMaxThreads(10, 10);//限制最大工作线程和i/o线程
ThreadPool.QueueUserWorkItem(new WaitCallback((a) =>
{
ConcurrentDictionary<string, SendingResult> test2 = new ConcurrentDictionary<string, SendingResult>();
test2.TryAdd(Guid.NewGuid().ToString(), new SendingResult
{
BatchNumber = Guid.NewGuid().ToString(),
DbName = "zzl",
EndId = 1,
StartId = 1,
TableName = "zzl",
OccurDate = DateTime.Now,
});
})); if (DateTime.Now.Minute == 02)
{
break;
}
}
查看一个任务管理器
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" 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当我把工作线程做了限制后,这种情况得到了改善
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" 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而如果对于操作频繁(轮训服务)的工作,如果不使用多线程,反而根据不吃什么内存,性能反而更好!
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" alt="" />
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