Notes about Cutting-Edge Technologies and Everything

Hey I just met you The network's laggy But here's my data So store it maybe (Kyle Kingsbury, Carly Rae Jepsen and the Perils of Network Partitions)

Some time ago I came across very interesting article by Konstantin V. Shvachko (now Senior Staff Software Engineer at LinkedIn) concerning the limits of hadoop scalability. The main conclusion of it is that "a 10,000 node HDFS cluster with a single name-node is expected to handle well a workload of 100,000 readers, but even 10,000 writers can produce enough workload to saturate the name-node, making it a bottleneck for linear scaling. Such a large difference in performance is attributed to get block locations (read workload) being a memory-only operation, while creates (write workload) require journaling, which is bounded by the local hard drive performance. There are ways to improve the single name-node performance, but any solution intended for single namespace server optimization lacks scalability." Konstantin continues: "The most promising solutions seem to be based on distributing the namespace server itself both for workload balancing and for reducing the si