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Session is scoped to a single client connection and basically ensures a read-your-own-writes consistency for each client; it is the default consistency level [15] Bounded staleness augments consistent prefix by ensuring that reads won't lag beyond x versions of an item or some specified time window
Highly available distributed real-time in-memory NoSQL database. Often used with MySQL for SQL cross-shard parallel query processing. OmniSci: OmniSci (formerly MapD) 2013 Open Source (Apache License 2.0) GPU-accelerated, SQL database and visualization platform for real-time analytics. Product consists of the core database plus a BI ...
A parallel database system seeks to improve performance through parallelization of various operations, such as loading data, building indexes and evaluating queries. [1] Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations.
A query includes a list of columns to include in the final result, normally immediately following the SELECT keyword. An asterisk ("*") can be used to specify that the query should return all columns of the queried tables. SELECT is the most complex statement in SQL, with optional keywords and clauses that include:
Under HTTP 1.0, connections should always be closed by the server after sending the response. [1]Since at least late 1995, [2] developers of popular products (browsers, web servers, etc.) using HTTP/1.0, started to add an unofficial extension (to the protocol) named "keep-alive" in order to allow the reuse of a connection for multiple requests/responses.
HTTP pipelining is a feature of HTTP/1.1, which allows multiple HTTP requests to be sent over a single TCP connection without waiting for the corresponding responses. [1] HTTP/1.1 requires servers to respond to pipelined requests correctly, with non-pipelined but valid responses even if server does not support HTTP pipelining.
Elementary teacher Amy McMahon is begging parents to stop sending their kids to school with syrup-filled fruit cups for lunch or snack.
In parallel programming, the code is divided into threads. The read-write conflicting variables are split between threads and each thread has a copy of them. Data structures such as linked lists , trees , and hash tables have data variables that are linked and cannot be split between threads; hence, implementing parallelism is very difficult. [ 6 ]