pymongo | 易学教程

MongoDB: How to query a time-series with incomplete data?

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问题 I'm storing time series data in a mongoDB collection with one data point every 15min. But sometimes, due to bad conditions, some data points get lost. I have a dataset as follows: {"device_id": "ABC","temp": 12,"timestamp": 2020-01-04T17:48:09.000+00:00} {"device_id": "ABC","temp": 10,"timestamp": 2020-01-04T18:03:09.000+00:00} {"device_id": "ABC","temp": 14,"timestamp": 2020-01-04T18:18:09.000+00:00} missing frame missing frame {"device_id": "ABC","temp": 13,"timestamp": 2020-01-04T19:03:09

MongoDB 学习

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阅读目录一简介二 MongoDB基础知识三安装四基本数据类型五 CRUD操作六可视化工具七 pymongo 一简介 MongoDB是一款强大、灵活、且易于扩展的通用型数据库 1、易用性 MongoDB是一个面向文档（document- oriented）的数据库，而不是关系型数据库。不采用关系型主要是为了获得更好得扩展性。当然还有一些其他好处，与关系数据库相比，面向文档的数据库不再有“行“（row）的概念取而代之的是更为灵活的“文档”（document）模型。通过在文档中嵌入文档和数组，面向文档的方法能够仅使用一条记录来表现复杂的层级关系，这与现代的面向对象语言的开发者对数据的看法一致。另外，不再有预定义模式（predefined schema）：文档的键（key）和值（value）不再是固定的类型和大小。由于没有固定的模式，根据需要添加或删除字段变得更容易了。通常由于开发者能够进行快速迭代，所以开发进程得以加快。而且，实验更容易进行。开发者能尝试大量的数据模型，从中选一个最好的。 2、易扩展性应用程序数据集的大小正在以不可思议的速度增长。随着可用带宽的增长和存储器价格的下降，即使是一个小规模的应用程序，需要存储的数据量也可能大的惊人，甚至超出了很多数据库的处理能力。过去非常罕见的T级数据，现在已经是司空见惯了。由于需要存储的数据量不断增长

mongodb slice - remove last n elements

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问题 Supposing I have the following array: { data: [1, 0, 4, 0, 0, 4, 1, 3, 0, 1, 0, 2, 2, 0, 1, 1, 0, 2, 0, 4, 1, 1, 0, 1, 1, 0] } How can I select all the elements, except the last 3 ? Using db.find({},{ "_id": 0, "data": {'$slice': [-3, 3] }}) I can exclude the last 3 elements, however I cannot select all the others, because if skip is negative or |skip| is higher than list.length then it returns the last three elements as though skip==0 How can I select all the elements, except the last 3 ?

pymongo bulk write perform very slow

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问题 We have a dataframe of almost 100000 records which i want to upsert in a mongodb collection. My sample code is mentioned below. For keeping it simple in below code, I am generating these data in a for loop and appending lstValues. In actual application, we receive these data from external csv files which we load it into pandas dataframe. We receive almost 98000 records from these external csv files. Also our original mongodb collection already contains almost 1,00,00,00 records and it keeps

pymongo bulk write perform very slow

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Name clash of two different bson modules - How can I use both pymongo's bson module and bson's bson module in the same script?

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问题 How to avoid the name clash of pymongo's bson module and bson's (py-bson on GitHub) bson module? 回答1: Install bson package as pybson , see https://github.com/py-bson/bson/issues/70. I have used pip uninstall bson and pip install pybson now so that I can use import pybson as bson when I want the old name back. If I accidentally need both pymongo 's and pybson 's import bson , I can use aliases. 来源： https://stackoverflow.com/questions/63068007/name-clash-of-two-different-bson-modules-how-can-i

Name clash of two different bson modules - How can I use both pymongo's bson module and bson's bson module in the same script?

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pymongo bulk write perform very slow

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Name clash of two different bson modules - How can I use both pymongo's bson module and bson's bson module in the same script?

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pymongo bulk write perform very slow

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