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Edna is a system that helps web applications allow users to remove their data without permanently losing their accounts, anonymize their old data, and selectively dissociate personal data from public profiles. Edna helps developers support these features while maintaining application functionality and referential integrity via disguising and revealing transformations. Disguising selectively renders user data inaccessible via encryption, and revealing enables the user to restore their data to the application. Edna's techniques allow transformations to compose in any order, e.g., deleting a previously anonymized user's account, or restoring an account back to an anonymized state. Experiments with Edna that add disguising and revealing transformations to three real-world applications show that Edna enables new privacy features in existing applications with low developer effort, is simpler than alternative approaches, and adds limited overhead to applications. 

Main-memory multicore transactional systems have achieved excellent performance using single-version optimistic concurrency control (OCC), especially on uncontended workloads. Nevertheless, systems based on other concurrency control protocols, such as hybrid OCC/ locking and variations on multiversion concurrency control (MVCC), are reported to outperform the best OCC systems, especially with increasing contention. This paper shows that implementation choices unrelated to concurrency control can explain some of these performance differences. Our evaluation shows the strengths and weaknesses of OCC, MVCC, and TicToc concurrency control under varying workloads and contention levels, and the importance of several implementation choices called basis factors. Given sensible basis factor choices, OCC performance does not collapse on high-contention TPC-C. We also present two optimization techniques, deferred updates and timestamp splitting, that can dramatically improve the high-contention performance of both OCC and MVCC. These techniques are known, but we apply them in a new context and highlight their potency: when combined, they lead to performance gains of 4.74× for MVCC and 5.01× for OCC in a TPC-C workload. 

A multiverse database transparently presents each application user with a flexible, dynamic, and independent view of shared data. This transformed view of the entire database contains only information allowed by a centralized and easily-auditable privacy policy. By enforcing the privacy policy once, in the database, multiverse databases reduce programmer burden and eliminate many frontend bugs that expose sensitive data. Multiverse databases' per-user transformations risk expensive queries if applied dynamically on reads, or impractical storage requirements if the database proactively materializes policy-compliant views. We propose an efficient design based on a joint dataflow across "universes" that combines global, shared computation and cached state with individual, per-user processing and state. This design, which supports arbitrary SQL queries and complex policies, imposes no performance overhead on read queries. Our early prototype supports thousands of parallel universes on a single server. 

Noria, first presented at OSDI ’18, is a new web application backend that delivers the same fast reads as an in-memory cache in front of the database, but without the application having to manage the cache. Even better, Noria still accepts SQL queries and allows changes to the queries without extra effort, just like a database. Noria performs well: it serves up to 14M requests per second on a single server, and supports a 5x higher load than carefully hand-tuned queries issued to MySQL. 

We introduce partially-stateful data-flow, a new streaming data-flow model that supports eviction and reconstruction of data-flow state on demand. By avoiding state explosion and supporting live changes to the data-flow graph, this model makes data-flow viable for building long-lived, low-latency applications, such as web applications. Our implementation, Noria, simplifies the back-end infrastructure for read-heavy web applications while improving their performance. A Noria application supplies a relational schema and a set of parameterized queries, which Noria compiles into a data-flow program that pre-computes results for reads and incrementally applies writes. Noria makes it easy to write high-performance applications without manual performance tuning or complex-to-maintain caching layers. Partial statefulness helps Noria limit its in-memory state without prior data-flow systems' restriction to windowed state, and helps Noria adapt its data-flow to schema and query changes while on-line. Unlike prior data-flow systems, Noria also shares state and computation across related queries, eliminating duplicate work. On a real web application's queries, our prototype scales to 5x higher load than a hand-optimized MySQL baseline. Noria also outperforms a typical MySQL/memcached stack and the materialized views of a commercial database. It scales to tens of millions of reads and millions of writes per second over multiple servers, outperforming a state-of-the-art streaming data-flow system. 

We introduce partially-stateful data-flow, a new streaming data-flow model that supports eviction and reconstruction of data-flow state on demand. By avoiding state explosion and supporting live changes to the data-flow graph, this model makes data-flow viable for building long-lived, low-latency applications, such as web applications. Our implementation, Noria, simplifies the backend infrastructure for read-heavy web applications while improving their performance. A Noria application supplies a relational schema and a set of parameterized queries, which Noria compiles into a data-flow program that pre-computes results for reads and incrementally applies writes. Noria makes it easy to write high-performance applications without manual performance tuning or complex-to-maintain caching layers. Partial statefulness helps Noria limit its in-memory state without prior data-flow systems’ restriction to windowed state, and helps Noria adapt its data-flow to schema and query changes while on-line. Unlike prior data-flow systems, Noria also shares state and computation across related queries, eliminating duplicate work. On a real web application’s queries, our prototype scales to 5× higher load than a hand-optimized MySQL baseline. Noria also outperforms a typical MySQL/memcached stack and the materialized views of a commercial database. It scales to tens of millions of reads and millions of writes per second over multiple servers, outperforming a state-of-the-art streaming data-flow system. ISBN 978-1-931971-47-8