圣诞快乐——向Google致敬——向linux致敬——向stackoverflow致敬——向openStack 致敬——永不退缩

There are 66 instances in Openstack Havana. I think these instances are zombies instance. Dashboard displays Terminate Success info when I click Terminate Instance. But the instance still exists on dashboard and its status is Running. I have already kill all qemu-kvm program on server.

In Mysql, database nova remains a lot of data. I don't know where to start to delete these data. Could someone give me some advice ?? Thanks a lot.

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up vote 2 down vote accepted

I did this in the Icehouse release of OpenStack, maybe you can map this to the Havana release:

  1. log into the database (you should see > mysql in your console)
  2. select the nova database:

    use nova;

  3. mark the rows in table instances as deleted (that's a "soft-delete")

    update instances set deleted_at = updated_at, deleted = id, power_state = 0, vm_state = "deleted", terminated_at = updated_at, root_device_name = NULL, task_state = NULL where deleted = 0;

    <-- That 'deletes' ALL your instances! Use show columns from instances; if you want to choose another column(s) for your where-clause.

  4. update the cache in table instance_info_chaches appropriately

    update instance_info_caches set deleted_at = updated_at, deleted = id where deleted = 0;

  5. update the fixed_ips table:

    update fixed_ips set instance_id = NULL, allocated = 0, virtual_interface_id = NULL where deleted = 0;

Note: If the column deleted contains a value not equal to zero, then this seems to be the way to say this row is supposed to be deleted. When I delete an instance via API, OpenStack seems to choose the id as value for deleted.

Source: http://www.databaseskill.com/4605135/

本研究利用Sen+MK方法分析了特定区域内的ET(蒸散发)趋势,重点评估了使用遥感数据的ET空间变化。该方法结合了Sen斜率估算器和Mann-Kendall(MK)检验,为评估长期趋势提供了稳健的框架,同时考虑了时间变化和统计显著性。 主要过程与结果: 1.ET趋势可视化:研究利用ET数据,通过ET-MK和ET趋势图展示了蒸散发在不同区域的空间和时间变化。这些图通过颜色渐变表示不同的ET水平及其趋势。 2.Mann-Kendall检验:应用MK检验来评估ET趋势的统计显著性。检验结果以二元分类图呈现,标明ET变化的显著性,帮助识别出有显著变化的区域。 3.重分类结果:通过重分类处理,将区域根据ET变化的显著性进行分类,从而聚焦于具有显著变化的区域。这一过程确保分析集中在具有实际意义的发现上。 4.最终输出:最终结果以栅格图和png图的形式呈现,支持各种应用,包括政策规划、水资源管理和土地利用变化分析,这些都是基于详细的时空分析。 ------------------------------------------------------------------- 文件夹构造: data文件夹:原始数据,支持分析的基础数据(MOD16A2H ET数据 宁夏部分)。 results文件夹:分析结果与可视化,展示研究成果。 Sen+MK_optimized.py:主分析脚本,适合批量数据处理和自动化分析。 Sen+MK.ipynb:Jupyter Notebook,复现可视化地图。
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