Ramblings on serializability

-
Here is a very raw/immature idea I have been toying with recently. I decided to write it down and share in order to get feedback about whether this is worth exploring further.

Serializability

Serializability of reads and writes (sequential consistency) is an important feature in distributed systems. A significant application of serializability is in transaction processing in distributed databases (e.g., Spanner).

Paxos serialization versus serializability

Paxos is a method for fault-tolerant state machine replication. In order to achieve fault-tolerant state machine replication, Paxos employs consensus to serialize operations at a leader and apply the operations at each replica in this exact serialized order (dictated by the leader).

While serialization is not an end in Paxos but rather a means, Paxos is seen nowadays as a defacto method for serialization rather than a method for fault-tolerant state machine replication. Maybe the ZooKeeper implementation of a Paxos-based lock-service help promote this confusion and blur the lines between Paxos's true goal (fault-tolerant replication) with its side effect (serialization).

In fact Paxos serialization is overkill, it is too strong. Paxos will serialize operations in a total order, which is not necessarily needed for sequential consistency. Today in many applications where knowing the total order and replicated-logging of that order is not important, Paxos is still (ab)used.

Serialization is not and should not be tightly-related to a replication solution.

OK, so what? (What is wrong with using a drug for its side effect?)

This confusion may permeate the misconception that serialization is inherently a reactive process. Many people have now been thinking about serialization from the Paxos perspective and as an inherently on-demand process.

(Probably there are other problems that arise due to this confusion, but for now I am only picking on this one.)

Proactive serialization

Serialization can actually be proactive and anticipatory. The workers does not need to make a serialization request to a Paxos leader. By getting rid of such a request (albeit in a fraction of the cases), latency can be reduced and throughput can be improved.

By adopting the proactive serialization philosophy, a lock service can provide the locks to some workers proactively so those workers can go ahead. Embracing this philosophy, a lock-service master can anticipate a future request and provide some locks ahead of time. The benefit of this is to eliminate the need for an explicit request (again in a fraction of the cases) and improve throughput and reduce latency.

A couple paragraphs above I said that "Today in many applications where knowing the total order and replicated-logging of that order is not important, Paxos is still (ab)used." Picking up on that thread I will claim further (without much evidence for now) that in those cases, proactive serialization could do a better job.

What are some ways to achieve proactive serialization?

How can proactive serialization be achieved? One approach is to employ machine learning. The lock service learns the patterns of requests for locks over time and then starts distributing these locks speculatively before they are requested.

Employing presignaling can be another approach to achieve proactive serialization. The nodes can anticipate which locks they will be needing in the next round or minute and ask for those locks in bulk speculatively. The lock service can choose to honor some of these requests and achieve proactive serialization to improve performance.

Another approach to achieve proactive serialization can be to do a static analysis of workers' programs/actions and come up with patterns/sequence of accesses. When the lock service observes one of the detected patterns, it can give the locks in advance to the respective workers that are mentioned in the rest of the pattern.

Did I pick on Paxos unfairly?

Actually, none of these proactive approaches are ruled out in Paxos. The Paxos leader itself could be making these proactive/speculative lock giving requests in advance. So, did I really need to pick on Paxos? Maybe not.

However, Paxos serialization in total order is still overkill and can cause problems in a Paxos-based solution. Google Spanner used a smart solution of assigning separate conflict domains (at the tablet level) to Paxos groups. This way it was able to provide locks in parallel across separate conflict domains.

If we do not tightly-couple serialization with a Paxos-based replication service, we can find more efficient and new solutions for serialization.

Comments

Murat said…
In response to questions posed here,
http://nosql.mypopescu.com/post/56145603298/paxos-serialization-serializability-and-proactive
I posted the following comment.

The lock service can be implemented distributedly and does not necessarily have a master.

Sorry, I should have been more clear. What I had in mind was to give out locks on a lease. And even then the lock service can revoke the locks by negotiating with the node; If the node that a lock is leased to is not using it, and another node requests, lock service can request it back to give to the other node.

I am hoping that it could be possible to implement this proactive leasing part as "hints" as defined in the Hints for computer system design.

http://muratbuffalo.blogspot.com/2011/01/hints-for-computer-system-design-acm.html

Use hints to speed up normal execution: A hint, like a cache entry, is the saved result of some computation. It is different in two ways: it may be wrong, and it is not necessarily reached by an associative lookup. Because a hint may be wrong, there must be a way to check its correctness before taking any unrecoverable action. It is checked against the 'truth', information that must be correct but can be optimized for this purpose rather than for efficient execution. Like a cache entry, the purpose of a hint is to make the system run faster. Usually this means that it must be correct nearly all the time. Hints are very relevant for speculative execution, and you can find several examples of hints and speculative execution in computer systems. One example of a hint is in the Ethernet, in which lack of a carrier signal on the cable is used as a hint that a packet can be sent. If two senders take the hint simultaneously, there is a collision that both can detect; both stop, delay for a randomly chosen interval, and then try again.
July 23, 2013 at 2:06 AM
Post a Comment

Popular posts from this blog

Hints for Distributed Systems Design

-
This is with apologies to Butler Lampson, who published the " Hints for computer system design " paper 40 years ago in SOSP'83. I don't claim to match that work of course. I just thought I could draft this post to organize my thinking about designing distributed systems and get feedback from others. I start with the same  disclaimer Lampson gave. These hints are not novel, not foolproof recipes, not laws of design, not precisely formulated, and not always appropriate. They are just hints.  They are context dependent, and some of them may be controversial. That being said, I have seen these hints successfully applied in distributed systems design throughout my 25 years in the field, starting from the theory of distributed systems (98-01), immersing into the practice of wireless sensor networks (01-11), and working on cloud computing systems both in the academia and industry ever since. These heuristic principles have been applied knowingly or unknowingly and has proven
Read more >>

Learning about distributed systems: where to start?

-
This is definitely not a "learn distributed systems in 21 days" post. I recommend a principled, from the foundations-up, studying of distributed systems, which will take a good three months in the first pass, and many more months to build competence after that. If you are practical and coding oriented you may not like my advice much. You may object saying, "Shouldn't I learn distributed systems with coding and hands on? Why can I not get started by deploying a Hadoop cluster, or studying the Raft code." I think that is the wrong way to go about learning distributed systems, because seeing similar code and programming language constructs will make you think this is familiar territory, and will give you a false sense of security. But, nothing can be further from the truth. Distributed systems need radically different software than centralized systems do.  --A. Tannenbaum This quotation is literally the first sentence in my distributed systems syllabus. Inst
Read more >>

Making database systems usable

-
Image
C. J. Date's Sigmod 1983 keynote, "Database Usability", was prescient. Usability is the most important thing to the customers. They care less about impressive benchmarks or clever algorithms, and more about whether they can operate and use a database efficiently to query, update, analyze, and persist their data with minimal headache. (BTW, does anyone have a link to the contents of this Sigmod'83 talk? There is no transcript around, except for this short abstract .) The paper we cover today is from Sigmod 2007. It takes on the database usability problem raised in that 1983 keynote head-on, and calls out that the king is still naked.  Let's give some context for the year 2007. Yes, XML format was still popular then. The use-case in the paper is XQuery. The paper does not contain any  reference to json. MongoDB would be released in 2009 with the document model; and that seems to be great timing for some of the usability pains mentioned in the paper! Web 2.0 was in
Read more >>

Looming Liability Machines (LLMs)

-
As part of our zoom reading group ( wow, 4.5 years old now ), we discussed a paper that uses LLMs for automatic root cause analysis (RCA) for cloud incidents. This was a pretty straightforward application of LLMs. The proposed system employs an LLM to match incoming incidents to incident handlers based on their alert types, predicts the incident's root cause category, and provides an explanatory narrative. The only customization is through prompt-engineering. Since this is a custom domain, I think a more principled and custom-designed  machine learning system would be more appropriate rather than adopting LLMs. Anyways, the use of LLMs for RCAs spooked me vicerally. I couldn't find the exact words during the paper discussion, but I can articulate this better now. Let me explain. RCA is serious business Root cause analysis (RCA) is the process of identifying the underlying causes of a problem/incident, rather than just addressing its symptoms. One RCA heuristic is asking 5 Why&#
Read more >>

Foundational distributed systems papers

-
I talked about the importance of reading foundational papers last week. To followup, here is my compilation of foundational papers in the distributed systems area. (I focused on the core distributed systems area, and did not cover networking, security, distributed ledgers, verification work etc. I even left out distributed transactions, I hope to cover them at a later date.)  I classified the papers by subject, and listed them in chronological order. I also listed expository papers and blog posts at the end of each section. Time and State in Distributed Systems Time, Clocks, and the Ordering of Events in a Distributed System. Leslie Lamport, Commn. of the ACM,  1978. Distributed Snapshots: Determining Global States of a Distributed System. K. Mani Chandy Leslie Lamport, ACM Transactions on Computer Systems, 1985. Virtual Time and Global States of Distributed Systems.  Mattern, F. 1988. Practical uses of synchronized clocks in distributed systems. B. Liskov, 1991. Expository papers
Read more >>

Advice to the young

-
Image
I notice I haven't written any advice posts recently. Here is a collection of my advice posts pre 2020. I've been feeling all this elderly wisdom pent up in me, ready to pour at any moment. So here it goes. Get ready to quench your thirst from my fount of wisdom. No man, think for yourself, only get what works for you. It is called foundations, not theory Foundations of computer science (or rather any field of study) are the most important topics you can learn. These lay down the frame of thinking/perspective for that area of study. Yet, I am saddened to hear these called as "theory", and labeled as "unpractical". This couldn't be farther from the truth. Take a look at how I recommend studying distributed systems . Don't you dare call this "theory" and "unpractical". This lays the bedrock that you build your practice on. Don't skimp on the foundations. Don't build your home on quicksand. Keep your hands dirty, your mind cl
Read more >>

Linearizability: A Correctness Condition for Concurrent Objects

-
Image
This paper is from Herlihy and Wing appeared in ACM Transactions on Programming Languages and Systems 1990. This is the canonical reference for the linearizability definition. I had not read this paper in detail before, so I thought it would be good to go to the source to see if there are additional delightful surprises in the original text. Hence, this post. I will dive into a technical analysis of the paper first, and then discuss some of my takes toward the end. I had written an accessible explanation of linearizability earlier; you may want to read that first. I will assume an understanding of linearizability to keep this review at reasonable length. Introduction I love how the old papers just barge in with the model, without bothered by pleasantries such as motivation of the problem. These are the first two sentences of the introduction. "A concurrent system consists of a collection of sequential processes that communicate through shared typed objects . This model encompass
Read more >>

Scalable OLTP in the Cloud: What’s the BIG DEAL?

-
Image
This paper is from Pat Helland, the apostate philosopher of database systems, overall a superb person, and a good friend of mine. The paper appeared this week at CIDR'24. (Check out the program for other interesting papers). The motivating question behind this work is: " What are the asymptotic limits to scale for cloud OLTP (OnLine Transaction Processing) systems? " Pat says that the CIDR 2023 paper "Is Scalable OLTP in the Cloud a Solved Problem?" prompted this question.  The answer to the question? Pat says that the answer lies in the joint responsibility of database and the application. If you know of Pat's work, which I have summarized several in this blog , you would know that Pat has been advocating along these lines before. But this paper provides a very crisp, specific, concrete answer. Read on for my summary of the paper. Disclaimer: This is a wisdom and technical information/detail packed 13-page paper, so I will try my best to summarize the sa
Read more >>

Understanding the Performance Implications of Storage-Disaggregated Databases

-
Image
Storage-compute disaggregation in databases has emerged as a pivotal architecture in cloud environments, as evidenced by Amazon ( Aurora ), Microsoft ( Socrates ), Google (AlloyDB), Alibaba ( PolarDB ), and Huawei (Taurus). This approach decouples compute from storage, allowing for independent and elastic scaling of compute and storage resources. It provides fault-tolerance at the storage level. You can then share the storage for other services, such as adding read-only replicas for the databases. You can even use the storage level for easier sharding of your database. Finally, you can also use this for exporting a changelog asynchronously to feed into peripheral cloud services, such as analytics. Disaggregated architecture was the topic of Sigmod 23 panel . I think this quote summarizes the industry's thinking on the topic. "Disaggregated architecture is here, and is not going anywhere. In a disaggregated architecture, storage is fungible, and computing scales independently.
Read more >>

Designing Data Intensive Applications (DDIA) Book

-
Image
We started reading this book as part of Alex Petrov's book club . We just got started, so you can join us, by joining the discord channel above. We meet Wednesday's 11am Eastern Time.  Previously we had read transaction processing book by Grey and Reuters. This page links to my summaries of that book. Chp 1. Reliable, Scalable, and Maintainable Applications I love the diagrams opening each chapter. Beautiful! The first chapter consists of warm up stuff. It talks about the definitions of reliabilty, scalability, and maintainability. It is still engaging, because  it is written with an educator and technical blogger voice, rather than a dry academic voice. This book came out on 2017. Martin is working on the new version. So if you have comments for things to focus on for the new version, it would be helpful to collect them in a document and email it to Martin. For example, I am curious about how the below paragraph from the Preface will get revised with 8 more years of hindsight:
Read more >>