How to seamlessly migrate hundreds of millions of MySQL data to mongodb?

InfoQ 2020-11-10 08:23:19
seamlessly migrate hundreds millions mysql


{"type":"doc","content":[{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":" Inside the good doctor line ,S3 The system is responsible for the centralized storage of operation logs of all business parties 、 Query and manage . at present , The system has tens of millions of queries per day , Hundreds of thousands of insertions . As the amount of logs continues to accumulate , The main table has reached billions , A single table takes up disk space 400G+.S3 It's a system that existed early in the business , At that time, for the sake of simple and quick landing , Used Mysql To store , As the business grows , At the same time, performance and scalability should be considered , It's time to retype ."}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":" The new project is named :LogStore."}]}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":" The goal is "}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"1、 Security "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"S3 The system is at the beginning of design , Data isolation is not considered by business system , It's a direct use of key( System + Class name + id) + Finite fixed fields + serialize value The way to store , This method is obviously not convenient for subsequent cluster splitting and management .LogStore The system should divide the data area logically , The service side should specify when accessing app Verify the necessary permissions , To differentiate between different business data , Then insert and query ."}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"2、 generality "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"S3 It mainly provides one kind of 3 The layer structure , use MySQL Fixed fields for storage , This will inevitably cause a waste of field space .LogStore The system needs to provide a general log storage format , It is up to the business party to define the meaning of the field , And keep a certain degree of query dimension ."}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"3、 High performance "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"S3 Systematic QPS stay 300+, The single data is the largest 1KB about .LogStore The system should support the current QPS 10 More than times the speed of writing and reading ."}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"4、 Auditable "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":" To meet the requirements of internal security audit ,LogStore The system does not provide updates to the data , Only data insertion and query are allowed ."}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"5、 Easy to expand "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"LogStore The system and the underlying storage should be scalable , It can be expanded online , Meet the company's future 5 Log storage requirements for years or more , And to maximize disk space savings ."}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":" Scheme selection "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":" In order to achieve the goal of transformation , This paper investigates four storage transformation schemes , The comparison of various schemes is as follows :"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https:\/\/static001.geekbang.org\/resource\/image\/18\/c0\/1825bc742e3f0174b0274ff1ee8ccbc0.png","alt":null,"title":"","style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":"","fromPaste":false,"pastePass":false}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"1、 We don't fit — Sub database and sub table "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}
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