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Pyramid codes: Flexible schemes to trade space for access efficiency in reliable data storage systems
- In Proceedings of the IEEE International Symposium on Network Computing and Applications. IEEE, Los Alamitos
"... We design flexible schemes to explore the tradeoffs between storage space and access efficiency in reliable data storage systems. Aiming at this goal, two new classes of erasure-resilient codes are introduced – Basic Pyramid Codes (BPC) and Generalized Pyramid Codes (GPC). Both schemes require sligh ..."
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Cited by 81 (9 self)
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We design flexible schemes to explore the tradeoffs between storage space and access efficiency in reliable data storage systems. Aiming at this goal, two new classes of erasure-resilient codes are introduced – Basic Pyramid Codes (BPC) and Generalized Pyramid Codes (GPC). Both schemes require slightly more storage space than conventional schemes, but significantly improve the critical performance of read during failures and unavailability. As a by-product, we establish a necessary matching condition to characterize the limit of failure recovery, that is, unless the matching condition is satisfied, a failure case is impossible to recover. In addition, we define a maximally recoverable (MR) property. For all ERC schemes holding the MR property, the matching condition becomes sufficient, that is, all failure cases satisfying the matching condition are indeed recoverable. We show that GPC is the first class of non-MDS schemes holding the MR property.
XORing Elephants: Novel Erasure Codes for Big Data ⇤
"... Distributed storage systems for large clusters typically use replication to provide reliability. Recently, erasure codes have been used to reduce the large storage overhead of threereplicated systems. Reed-Solomon codes are the standard design choice and their high repair cost is often considered an ..."
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Cited by 59 (7 self)
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Distributed storage systems for large clusters typically use replication to provide reliability. Recently, erasure codes have been used to reduce the large storage overhead of threereplicated systems. Reed-Solomon codes are the standard design choice and their high repair cost is often considered an unavoidable price to pay for high storage e ciency and high reliability. This paper shows how to overcome this limitation. We present a novel family of erasure codes that are e ciently repairable and o↵er higher reliability compared to Reed-Solomon codes. We show analytically that our codes are optimal on a recently identified tradeo ↵ between locality and minimum distance. We implement our new codes in Hadoop HDFS and compare
Understanding network failures in data centers: measurement, analysis, and implications
- In Proc. of SIGCOMM. ACM
, 2011
"... We present the first large-scale analysis of failures in a data center network. Through our analysis, we seek to answer several fundamental questions: which devices/links are most unreliable, what causes failures, how do failures impact network traffic and how effective is network redundancy? We ans ..."
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Cited by 49 (3 self)
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We present the first large-scale analysis of failures in a data center network. Through our analysis, we seek to answer several fundamental questions: which devices/links are most unreliable, what causes failures, how do failures impact network traffic and how effective is network redundancy? We answer these questions using multiple data sources commonly collected by network operators. The key findings of our study are that (1) data center networks show high reliability, (2) commodity switches such as ToRs and AggS are highly reliable, (3) load balancers dominate in terms of failure occurrences with many short-lived software related faults, (4) failures have potential to cause loss of many small packets such as keep alive messages and ACKs, and (5) network redundancy is only 40 % effective in reducing the median impact of failure.
Simple Regenerating Codes: Network Coding for Cloud Storage
, 2011
"... Network codes designed specifically for distributed storage systems have the potential to provide dramatically higher storage efficiency for the same availability. One main challenge in the design of such codes is the exact repair problem: if a node storing encoded information fails, in order to ma ..."
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Cited by 39 (5 self)
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Network codes designed specifically for distributed storage systems have the potential to provide dramatically higher storage efficiency for the same availability. One main challenge in the design of such codes is the exact repair problem: if a node storing encoded information fails, in order to maintain the same level of reliability we need to create encoded information at a new node. One of the main open problems in this emerging area has been the design of simple coding schemes that allow exact and low cost repair of failed nodes and have high data rates. In particular, all prior known explicit constructions have data rates bounded by 1/2. In this paper we introduce the first family of distributed storage codes that have simple look-up repair and can achieve arbitrarily high rates. Our constructions are very simple to implement and perform exact repair by simple XORing of packets. We experimentally evaluate the proposed codes in a realistic cloud storage simulator and show significant benefits in both performance and reliability compared to replication and standard Reed-Solomon codes.
Themis: An I/O-Efficient MapReduce
"... “Big Data ” computing increasingly utilizes the MapReduce programming model for scalable processing of large data collections. Many MapReduce jobs are I/O-bound, and so minimizing the number of I/O operations is critical to improving their performance. In this work, we present Themis, a MapReduce im ..."
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Cited by 23 (3 self)
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“Big Data ” computing increasingly utilizes the MapReduce programming model for scalable processing of large data collections. Many MapReduce jobs are I/O-bound, and so minimizing the number of I/O operations is critical to improving their performance. In this work, we present Themis, a MapReduce implementation that reads and writes data records to disk exactly twice, which is the minimum amount possible for data sets that cannot fit in memory. In order to minimize I/O, Themis makes fundamentally different design decisions from previous MapReduce implementations. Themis performs a wide variety of MapReduce jobs – including click log analysis, DNA read sequence alignment, and PageRank – at nearly the speed of TritonSort’s record-setting sort performance [29].
2011. In search of I/O-optimal recovery from disk failures
- In Proceedings of the USENIX Workshop on Hot Topics in Storage and File Systems
"... We address the problem of minimizing the I/O needed to recover from disk failures in erasure-coded storage systems. The principal result is an algorithm that finds the optimal I/O recovery from an arbitrary number of disk failures for any XOR-based erasure code. We also describe a family of codes wi ..."
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Cited by 21 (2 self)
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We address the problem of minimizing the I/O needed to recover from disk failures in erasure-coded storage systems. The principal result is an algorithm that finds the optimal I/O recovery from an arbitrary number of disk failures for any XOR-based erasure code. We also describe a family of codes with high-fault tolerance and low recovery I/O, e.g. one instance tolerates up to 11 failures and recovers a lost block in 4 I/Os. While we have determined I/O optimal recovery for any given code, it remains an open problem to identify codes with the best recovery properties. We describe our ongoing efforts toward characterizing space overhead versus recovery I/O tradeoffs and generating codes that realize these bounds. 1
A Solution to the Network Challenges of Data Recovery
- in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster”, in arXiv:1309.0186
, 2013
"... Erasure codes, such as Reed-Solomon (RS) codes, are being increasingly employed in data centers to combat the cost of reliably storing large amounts of data. Al-though these codes provide optimal storage efficiency, they require significantly high network and disk usage during recovery of missing da ..."
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Cited by 20 (3 self)
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Erasure codes, such as Reed-Solomon (RS) codes, are being increasingly employed in data centers to combat the cost of reliably storing large amounts of data. Al-though these codes provide optimal storage efficiency, they require significantly high network and disk usage during recovery of missing data. In this paper, we first present a study on the im-pact of recovery operations of erasure-coded data on the data-center network, based on measurements from Face-book’s warehouse cluster in production. To the best of our knowledge, this is the first study of its kind avail-able in the literature. Our study reveals that recovery of RS-coded data results in a significant increase in network traffic, more than a hundred terabytes per day, in a cluster storing multiple petabytes of RS-coded data. To address this issue, we present a new storage code using our recently proposed Piggybacking framework, that reduces the network and disk usage during recovery by 30 % in theory, while also being storage optimal and supporting arbitrary design parameters. The implemen-tation of the proposed code in the Hadoop Distributed File System (HDFS) is underway. We use the measure-ments from the warehouse cluster to show that the pro-posed code would lead to a reduction of close to fifty terabytes of cross-rack traffic per day. 1
PREFAIL: A Programmable Tool for Multiple-Failure Injection
"... As hardware failures are no longer rare in the era of cloud computing, cloud software systems must “prevail ” against multiple, diverse failures that are likely to occur. Testing software against multiple failures poses the problem of combinatorial explosion of multiple failures. To address this pro ..."
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Cited by 13 (2 self)
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As hardware failures are no longer rare in the era of cloud computing, cloud software systems must “prevail ” against multiple, diverse failures that are likely to occur. Testing software against multiple failures poses the problem of combinatorial explosion of multiple failures. To address this problem, we present PreFail, a programmable failure-injection tool that enables testers to write a wide range of policies to prune down the large space of multiple failures. We integrate PreFail to three cloud software systems (HDFS, Cassandra, and ZooKeeper), show a wide variety of useful pruning policies that we can write for them, and evaluate the speed-ups in testing time that we obtain by using the policies. In our experiments, our testing approach with appropriate policies found all the bugs that one can find using exhaustive testing while spending 10X–200X less time than exhaustive testing.
Thialfi: A Client Notification Service for Internet-Scale Applications
"... Ensuring the freshness of client data is a fundamental problem for applications that rely on cloud infrastructure to store data and mediate sharing. Thialfi is a notification service developed at Google to simplify this task. Thialfi supports applications written in multiple programming languages an ..."
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Cited by 13 (0 self)
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Ensuring the freshness of client data is a fundamental problem for applications that rely on cloud infrastructure to store data and mediate sharing. Thialfi is a notification service developed at Google to simplify this task. Thialfi supports applications written in multiple programming languages and running on multiple platforms, e.g., browsers, phones, and desktops. Applications register their interest in a set of shared objects and receive notifications when those objects change. Thialfi servers run in multiple Google data centers for availability and replicate their state asynchronously. Thialfi’s approach to recovery emphasizes simplicity: all server state is soft, and clients drive recovery and assist in replication. A principal goal of our design is to provide a straightforward API and good semantics despite a variety of failures, including server crashes, communication failures, storage unavailability, and data center failures. Evaluation of live deployments confirms that Thialfi is scalable, efficient, and robust. In production use, Thialfi has scaled to millions of users and delivers notifications with an average delay of less than one second.
Surviving failures in bandwidthconstrained datacenters
- In Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication, SIGCOMM ’12
, 2012
"... Abstract-Datacenter networks have been designed to tolerate failures of network equipment and provide sufficient bandwidth. In practice, however, failures and maintenance of networking and power equipment often make tens to thousands of servers unavailable, and network congestion can increase servi ..."
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Cited by 12 (1 self)
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Abstract-Datacenter networks have been designed to tolerate failures of network equipment and provide sufficient bandwidth. In practice, however, failures and maintenance of networking and power equipment often make tens to thousands of servers unavailable, and network congestion can increase service latency. Unfortunately, there exists an inherent tradeoff between achieving high fault tolerance and reducing bandwidth usage in network core; spreading servers across fault domains improves fault tolerance, but requires additional bandwidth, while deploying servers together reduces bandwidth usage, but also decreases fault tolerance. We present a detailed analysis of a large-scale Web application and its communication patterns. Based on that, we propose and evaluate a novel optimization framework that achieves both high fault tolerance and significantly reduces bandwidth usage in the network core by exploiting the skewness in the observed communication patterns.
