73,718 research outputs found
How Fast can a Distributed Atomic Read be?
We study efficient and robust implementations of an atomic read-write data structure over an asynchronous distributed message-passing system made of reader and writer processes, as well as failure prone server processes implementing the data structure. We determine the exact conditions under which every read operation involves one-round of communication with the servers. These conditions relate the number of readers to the tolerated number of faulty servers, in a general model with crash and arbitrary failures
MDCC: Multi-Data Center Consistency
Replicating data across multiple data centers not only allows moving the data
closer to the user and, thus, reduces latency for applications, but also
increases the availability in the event of a data center failure. Therefore, it
is not surprising that companies like Google, Yahoo, and Netflix already
replicate user data across geographically different regions.
However, replication across data centers is expensive. Inter-data center
network delays are in the hundreds of milliseconds and vary significantly.
Synchronous wide-area replication is therefore considered to be unfeasible with
strong consistency and current solutions either settle for asynchronous
replication which implies the risk of losing data in the event of failures,
restrict consistency to small partitions, or give up consistency entirely. With
MDCC (Multi-Data Center Consistency), we describe the first optimistic commit
protocol, that does not require a master or partitioning, and is strongly
consistent at a cost similar to eventually consistent protocols. MDCC can
commit transactions in a single round-trip across data centers in the normal
operational case. We further propose a new programming model which empowers the
application developer to handle longer and unpredictable latencies caused by
inter-data center communication. Our evaluation using the TPC-W benchmark with
MDCC deployed across 5 geographically diverse data centers shows that MDCC is
able to achieve throughput and latency similar to eventually consistent quorum
protocols and that MDCC is able to sustain a data center outage without a
significant impact on response times while guaranteeing strong consistency
The End of a Myth: Distributed Transactions Can Scale
The common wisdom is that distributed transactions do not scale. But what if
distributed transactions could be made scalable using the next generation of
networks and a redesign of distributed databases? There would be no need for
developers anymore to worry about co-partitioning schemes to achieve decent
performance. Application development would become easier as data placement
would no longer determine how scalable an application is. Hardware provisioning
would be simplified as the system administrator can expect a linear scale-out
when adding more machines rather than some complex sub-linear function, which
is highly application specific.
In this paper, we present the design of our novel scalable database system
NAM-DB and show that distributed transactions with the very common Snapshot
Isolation guarantee can indeed scale using the next generation of RDMA-enabled
network technology without any inherent bottlenecks. Our experiments with the
TPC-C benchmark show that our system scales linearly to over 6.5 million
new-order (14.5 million total) distributed transactions per second on 56
machines.Comment: 12 page
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