designing data intensive applications by martin kleppmann

Frankly, it is also a chance coincidence, in the postgraduate stage into the field of distributed systems learning. Whether it's large-scale storage or computing, its core is the need to use distributed technologies to leverage parallelism to address data-intensive applications. Recently began to chew this "designing

the database engine, which allows the database system to introduce performance improvements without requiring any changes to the query. However, SQL is more functionally limited and has limited flexibility, which gives the database more automatic space for optimization. Declarative languages are generally suitable for parallel execution because they specify only the pattern of the result, not the algorithm used to determine the result. 4. SummaryThe

architecture is very reasonable. However, because of the reasons mentioned above, we usually do not adopt the synchronous replication method. This results in significant inconsistencies in the data: if you perform the same query on both leader and Follwer, you may get different results because not all writes are fed back on the follower in real time. This inconsistency is only temporary, so this situation is called final consistency. For this situati

In the first part of "Designing Data-intensive Applications" (see above), the basic theory and knowledge of the data system are introduced, all based on single node. In the second part of the Ddia (distributed data), the field of

write transactions. If the database tracks the activity of each transaction in great detail, it can accurately determine which transactions need to be aborted, but these costs can become significant. Less verbose tracking of transactions can be faster, but may result in more transactions being aborted. A serializable isolation snapshot is advantageous compared to a two-phase lock: One transaction does not need to block locks that wait for another transaction to hold. Summary:In this article, we

PROTOCOLBUF and thrift. Each time the database schema changes, the administrator must manually update the mapping from the database column name to the field tag. And Avro is a simple mode conversion every time the runtime is run. Any program that reads a new data file will perceive that the record field has changed. 4. SummaryCoding details not only affect productivity, but more importantly, the architecture of