Too many processes already exist

本文介绍了一个Oracle用户登录异常的问题及解决过程。故障表现为Oracle用户无法登录,执行命令缓慢,而其他用户正常。通过检查发现Oracle进程过多导致系统限制,通过调整AIX系统的最大进程数解决了该问题。
故障发生时,主机oracle用户不能登录,数据库登陆异常,并且oracle帐号执行命令很慢,其他帐号正常。登录Oracle用户时提示错误ksh: 0403-030 The fork function failed. Too many processes already exist。 

   系统检查 

       1.> ps -ef |grep oracle |wc -l 

                       956        [有很多 oracle 44921036 1 0  0:00 进程

      2.> lsattr   -El   sys0 |grep maxuproc 

         maxuproc        945               

                         Maximum number of PROCESSES allowed per usere 

    一次原因:系统中用户最大进程数太少,需修改OSMaxuproc数量 

    系统修改: 

           1.> smitty chgsys 

     Maximum number of PROCESSES allowed per user       [3000] 

                | 

                   V 

     Maximum number of PROCESSES allowed per user       [3000] 

                

    结果: 

         一切正常,但是可以修改maxuproc=0,无限制?

 

IBM AIX:
lsattr -E -l sys0 | grep maxuproc    ---查看最大进程数
chdev -l sys0 -a maxuproc=1024     ---修改最大进程数

来自 “ ITPUB博客 ” ,链接:http://blog.itpub.net/13750068/viewspace-750693/,如需转载,请注明出处,否则将追究法律责任。

转载于:http://blog.itpub.net/13750068/viewspace-750693/

jzuser@vpc87-3:~/Work_dir/Gn/pystudy/NnuNet/nnUNet$ nnUNetv2_plan_and_preprocess -d 3 --verify_dataset_integrity --npfp 8 --npp 8 usage: nnUNetv2_plan_and_preprocess [-h] [-d D [D ...]] [-fpe FPE] [-npfp NPFP] [--verify_dataset_integrity] [--no_pp] [--clean] [-pl PL] [-gpu_memory_target GPU_MEMORY_TARGET] [-preprocessor_name PREPROCESSOR_NAME] [-overwrite_target_spacing OVERWRITE_TARGET_SPACING [OVERWRITE_TARGET_SPACING ...]] [-overwrite_plans_name OVERWRITE_PLANS_NAME] [-c C [C ...]] [-np NP [NP ...]] [--verbose] nnUNetv2_plan_and_preprocess: error: unrecognized arguments: --npfp 8 --npp 8 jzuser@vpc87-3:~/Work_dir/Gn/pystudy/NnuNet/nnUNet$ nnUNetv2_plan_and_preprocess -h usage: nnUNetv2_plan_and_preprocess [-h] [-d D [D ...]] [-fpe FPE] [-npfp NPFP] [--verify_dataset_integrity] [--no_pp] [--clean] [-pl PL] [-gpu_memory_target GPU_MEMORY_TARGET] [-preprocessor_name PREPROCESSOR_NAME] [-overwrite_target_spacing OVERWRITE_TARGET_SPACING [OVERWRITE_TARGET_SPACING ...]] [-overwrite_plans_name OVERWRITE_PLANS_NAME] [-c C [C ...]] [-np NP [NP ...]] [--verbose] options: -h, --help show this help message and exit -d D [D ...] [REQUIRED] List of dataset IDs. Example: 2 4 5. This will run fingerprint extraction, experiment planning and preprocessing for these datasets. Can of course also be just one dataset -fpe FPE [OPTIONAL] Name of the Dataset Fingerprint Extractor class that should be used. Default is 'DatasetFingerprintExtractor'. -npfp NPFP [OPTIONAL] Number of processes used for fingerprint extraction. Default: 8 --verify_dataset_integrity [RECOMMENDED] set this flag to check the dataset integrity. This is useful and should be done once for each dataset! --no_pp [OPTIONAL] Set this to only run fingerprint extraction and experiment planning (no preprocesing). Useful for debugging. --clean [OPTIONAL] Set this flag to overwrite existing fingerprints. If this flag is not set and a fingerprint already exists, the fingerprint extractor will not run. REQUIRED IF YOU CHANGE THE DATASET FINGERPRINT EXTRACTOR OR MAKE CHANGES TO THE DATASET! -pl PL [OPTIONAL] Name of the Experiment Planner class that should be used. Default is 'ExperimentPlanner'. Note: There is no longer a distinction between 2d and 3d planner. It's an all in one solution now. Wuch. Such amazing. -gpu_memory_target GPU_MEMORY_TARGET [OPTIONAL] DANGER ZONE! Sets a custom GPU memory target. Default: 8 [GB]. Changing this will affect patch and batch size and will definitely affect your models performance! Only use this if you really know what you are doing and NEVER use this without running the default nnU-Net first (as a baseline). -preprocessor_name PREPROCESSOR_NAME [OPTIONAL] DANGER ZONE! Sets a custom preprocessor class. This class must be located in nnunetv2.preprocessing. Default: 'DefaultPreprocessor'. Changing this may affect your models performance! Only use this if you really know what you are doing and NEVER use this without running the default nnU-Net first (as a baseline). -overwrite_target_spacing OVERWRITE_TARGET_SPACING [OVERWRITE_TARGET_SPACING ...] [OPTIONAL] DANGER ZONE! Sets a custom target spacing for the 3d_fullres and 3d_cascade_fullres configurations. Default: None [no changes]. Changing this will affect image size and potentially patch and batch size. This will definitely affect your models performance! Only use this if you really know what you are doing and NEVER use this without running the default nnU-Net first (as a baseline). Changing the target spacing for the other configurations is currently not implemented. New target spacing must be a list of three numbers! -overwrite_plans_name OVERWRITE_PLANS_NAME [OPTIONAL] uSE A CUSTOM PLANS IDENTIFIER. If you used -gpu_memory_target, -preprocessor_name or -overwrite_target_spacing it is best practice to use -overwrite_plans_name to generate a differently named plans file such that the nnunet default plans are not overwritten. You will then need to specify your custom plans file with -p whenever running other nnunet commands (training, inference etc) -c C [C ...] [OPTIONAL] Configurations for which the preprocessing should be run. Default: 2d 3f_fullres 3d_lowres. 3d_cascade_fullres does not need to be specified because it uses the data from 3f_fullres. Configurations that do not exist for some dataset will be skipped. -np NP [NP ...] [OPTIONAL] Use this to define how many processes are to be used. If this is just one number then this number of processes is used for all configurations specified with -c. If it's a list of numbers this list must have as many elements as there are configurations. We then iterate over zip(configs, num_processes) to determine then umber of processes used for each configuration. More processes is always faster (up to the number of threads your PC can support, so 8 for a 4 core CPU with hyperthreading. If you don't know what that is then dont touch it, or at least don't increase it!). DANGER: More often than not the number of processes that can be used is limited by the amount of RAM available. Image resampling takes up a lot of RAM. MONITOR RAM USAGE AND DECREASE -np IF YOUR RAM FILLS UP TOO MUCH!. Default: 8 4 8 (=8 processes for 2d, 4 for 3d_fullres and 8 for 3d_lowres if -c is at its default) --verbose Set this to print a lot of stuff. Useful for debugging. Will disable progrewss bar! Recommended for cluster environments 命令还是不对
08-22
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