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  • NoSQL for concurrent reads/writes

    - by Mickael Marrache
    After getting some performance issues for an application using a MySQL database, I'm thinking of using NoSQL solutions. My architecture is as follows: One application receives messages from the network at a high throughput (i.e. 50000 messages/sec). Each message is stored in the DB, so it's important for the write rate to be as fast as the arrival rate. Then, I also have some PHP pages that accesses the DB to get the data stored by the other application. It's important for me that the retrieved data is as relevant as possible (i.e. not old data, let's say not more than 5 seconds old). Also, the data is not critical, so I don't need any security mechanism to avoid losing the data. I see there are a lot of NoSQL solutions, but I don't know if they are all relevant. Could you please provide me some directions. Thanks

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  • PHP-friendly NoSQL solutions

    - by mattbasta
    I'm looking to use a NoSQL solution for my next project, which will be written in PHP. What choices do I have in terms of NoSQL solutions that can easily interfaced via PHP? I haven't done much thinking about the architecture yet, so I'm not sure what my needs will be; I'd simply like to know what my choices are so I don't build something I can't reasonably implement. For instance, I know Cassandra has Pandra, but that's just a PHP library. MongoDB has a native PECL extension.

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  • Which NoSQL db to use with C?

    - by systemsfault
    Hello all, I'm working on an application that I'm going to write with C and i am considering to use a nosql db for storing timeseries data with at most 8 or 9 fields. But in every 5 minutes there will huge write operations such as 2-10 million rows and then there will be reads(but performance is not as crucial in read as in the write operation). I'm considering to use a NoSQL db here in order to store the data but couldn't decide on which one to use. Couchdb seems to have a stable driver called pillowtalk for C; but Mongo's driver doesn't look as promising as pillowtalk. I'm also open to other suggestions. What is your recommendation?

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  • NoSQL for filesystem storage organization and replication?

    - by wheaties
    We've been discussing design of a data warehouse strategy within our group for meeting testing, reproducibility, and data syncing requirements. One of the suggested ideas is to adapt a NoSQL approach using an existing tool rather than try to re-implement a whole lot of the same on a file system. I don't know if a NoSQL approach is even the best approach to what we're trying to accomplish but perhaps if I describe what we need/want you all can help. Most of our files are large, 50+ Gig in size, held in a proprietary, third-party format. We need to be able to access each file by a name/date/source/time/artifact combination. Essentially a key-value pair style look-up. When we query for a file, we don't want to have to load all of it into memory. They're really too large and would swamp our server. We want to be able to somehow get a reference to the file and then use a proprietary, third-party API to ingest portions of it. We want to easily add, remove, and export files from storage. We'd like to set up automatic file replication between two servers (we can write a script for this.) That is, sync the contents of one server with another. We don't need a distributed system where it only appears as if we have one server. We'd like complete replication. We also have other smaller files that have a tree type relationship with the Big files. One file's content will point to the next and so on, and so on. It's not a "spoked wheel," it's a full blown tree. We'd prefer a Python, C or C++ API to work with a system like this but most of us are experienced with a variety of languages. We don't mind as long as it works, gets the job done, and saves us time. What you think? Is there something out there like this?

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  • New MySQL Cluster 7.3 Previews: Foreign Keys, NoSQL Node.js API and Auto-Tuned Clusters

    - by Mat Keep
    At this weeks MySQL Connect conference, Oracle previewed an exciting new wave of developments for MySQL Cluster, further extending its simplicity and flexibility by expanding the range of use-cases, adding new NoSQL options, and automating configuration. What’s new: Development Release 1: MySQL Cluster 7.3 with Foreign Keys Early Access “Labs” Preview: MySQL Cluster NoSQL API for Node.js Early Access “Labs” Preview: MySQL Cluster GUI-Based Auto-Installer In this blog, I'll introduce you to the features being previewed. Review the blogs listed below for more detail on each of the specific features discussed. Save the date!: A live webinar is scheduled for Thursday 25th October at 0900 Pacific Time / 1600UTC where we will discuss each of these enhancements in more detail. Registration will be open soon and published to the MySQL webinars page MySQL Cluster 7.3: Development Release 1 The first MySQL Cluster 7.3 Development Milestone Release (DMR) previews Foreign Keys, bringing powerful new functionality to MySQL Cluster while eliminating development complexity. Foreign Key support has been one of the most requested enhancements to MySQL Cluster – enabling users to simplify their data models and application logic – while extending the range of use-cases for both custom projects requiring referential integrity and packaged applications, such as eCommerce, CRM, CMS, etc. Implementation The Foreign Key functionality is implemented directly within the MySQL Cluster data nodes, allowing any client API accessing the cluster to benefit from them – whether they are SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA, HTTP/REST or the new Node.js API - discussed later.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation.  This represents a further enhancement to MySQL Cluster's support for on0line schema changes, ie adding and dropping indexes, adding columns, etc.  Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  Getting Started with MySQL Cluster 7.3 DMR1: Users can download either the source or binary and evaluate the MySQL Cluster 7.3 DMR with Foreign Keys now! (Select the Development Release tab). MySQL Cluster NoSQL API for Node.js Node.js is hot! In a little over 3 years, it has become one of the most popular environments for developing next generation web, cloud, mobile and social applications. Bringing JavaScript from the browser to the server, the design goal of Node.js is to build new real-time applications supporting millions of client connections, serviced by a single CPU core. Making it simple to further extend the flexibility and power of Node.js to the database layer, we are previewing the Node.js Javascript API for MySQL Cluster as an Early Access release, available for download now from http://labs.mysql.com/. Select the following build: MySQL-Cluster-NoSQL-Connector-for-Node-js Alternatively, you can clone the project at the MySQL GitHub page.  Implemented as a module for the V8 engine, the new API provides Node.js with a native, asynchronous JavaScript interface that can be used to both query and receive results sets directly from MySQL Cluster, without transformations to SQL. Figure 1: MySQL Cluster NoSQL API for Node.js enables end-to-end JavaScript development Rather than just presenting a simple interface to the database, the Node.js module integrates the MySQL Cluster native API library directly within the web application itself, enabling developers to seamlessly couple their high performance, distributed applications with a high performance, distributed, persistence layer delivering 99.999% availability. The new Node.js API joins a rich array of NoSQL interfaces available for MySQL Cluster. Whichever API is chosen for an application, SQL and NoSQL can be used concurrently across the same data set, providing the ultimate in developer flexibility.  Get started with MySQL Cluster NoSQL API for Node.js tutorial MySQL Cluster GUI-Based Auto-Installer Compatible with both MySQL Cluster 7.2 and 7.3, the Auto-Installer makes it simple for DevOps teams to quickly configure and provision highly optimized MySQL Cluster deployments – whether on-premise or in the cloud. Implemented with a standard HTML GUI and Python-based web server back-end, the Auto-Installer intelligently configures MySQL Cluster based on application requirements and auto-discovered hardware resources Figure 2: Automated Tuning and Configuration of MySQL Cluster Developed by the same engineering team responsible for the MySQL Cluster database, the installer provides standardized configurations that make it simple, quick and easy to build stable and high performance clustered environments. The auto-installer is previewed as an Early Access release, available for download now from http://labs.mysql.com/, by selecting the MySQL-Cluster-Auto-Installer build. You can read more about getting started with the MySQL Cluster auto-installer here. Watch the YouTube video for a demonstration of using the MySQL Cluster auto-installer Getting Started with MySQL Cluster If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3 and the Early Access previews). Or use the new MySQL Cluster Auto-Installer! Download the Guide to Scaling Web Databases with MySQL Cluster (to learn more about its architecture, design and ideal use-cases). Post any questions to the MySQL Cluster forum where our Engineering team and the MySQL Cluster community will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section here or in the blogs referenced in this article. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. The first Development Release of MySQL Cluster 7.3 and the Early Access previews give you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases, by using the comments of this blog.

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  • Help to choose NoSQL database for project

    - by potapuff
    There is a table: doc_id(integer)-value(integer) Approximate 100k doc_id and 27?? rows. Majority query on this table - searching documents similar to current document: select 10 documents with maximum of (count common to current document value)/(count ov values in document). Nowadays we use PostgreSQL. Table weight (with index) ~1,5 GB. Average query time ~0.5s. Should I transfer all this to NoSQL base, if so, what?

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  • Help to chouse NoSQL database for project

    - by potapuff
    There is a table: doc_id(integer)-value(integer) Approximate 100k doc_id and 27?? rows. Majority query on this table - searching documents similar to current document: select 10 documents with maximum of (count common to current document value)/(count ov values in document). Nowadays we use PostgreSQL. Table weight (with index) ~1,5 GB. Average query time ~0.5s. Should I transfer all this to NoSQL base, if so, what?

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  • Clojure and NoSQL databases

    - by Mad Wombat
    I am currently trying to pick between different NoSQL databases for my project. The project is being written in clojure and javascript. I am currently looking at three candidates for storage. What are the relative strengths and weaknesses of MongoDB, FleetDB and CouchDB? Which one is better supported in Clojure? Which one is better supported under Linux? Did I miss a better product (has to be free and OSS)?

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  • Why exactly do we use NoSQL?

    - by Tian H.
    Having understood some of the advantages that NoSQL offers (scalability, availability, etc.), I am still not clear why a website would want to use a non-relational database. Can I get some help on this, preferably with an example?

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  • NoSQL vs Relational Coding Styles

    - by Chris Henry
    When building objects that make use of data stored in a RDBMS, it's normally pretty clear what you're getting back, as dictated by the tables and columns being queried. However, when dealing with NoSQL, document-based systems, it's less clear what is being retrieved. What are common methods of keeping track of structure in which data is stored?

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  • NoSQL vs Ehcache caching advise for speeding up read only mysql Database

    - by paddydub
    I'm building a Route Planner Webapp using Spring/Hibernate/Tomcat and a mysql database, I have a database containing read only data, such as Bus Stop Coordinates, Bus times which is never updated. I'm trying to make the app run faster, each time the application is run it will preform approx 1000 reads to the database to calculate a route. I have setup a Ehcache which greatly improves the read from database times. I'm now setting terracotta + Ehcache distributed caching to share the cache with multiple Tomcat JVMs. This seems a bit complicated. I've tried memcached but it was not performing as fast as ehcache. I'm wondering if a MongoDb or Redis would be better suited. I have no experience with nosql but I would appreciate if anyone has any ideas. What i need is quick access to the read only database.

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  • Anyone using NoSQL databases for medical record storage?

    - by Brian Bay
    Electronic Medical records are composed of different types of data. Visit information ( date/location/insurance info) seems to lend itself to a RDMS. Other types of medical infomation, such as lab reports, x-rays, photos, and electronic signatures, are document based and would seem to be a good candidate for a 'document-oriented' database, such as MongoDB. Traditionally, binary data would be stored as a BLOB in a RDBMS. A hybrid approach using a traditional RDBMS along with a 'document-oriented' database would seem like good alternative to this. Other alternative would be something like DB2 purexml. The ultimate answer could be that 'it depends', but I really just wanted to get some general feedback/ideas on this. Is anyone using the NoSql approach for medical records?

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  • Are there any e-commerce websites that use NoSQL databases

    - by Saif Bechan
    I have read a lot lately about 'NoSQL' databases such as CouchDB, MongoDB etc. Most of the websites I have seen using this are mainly text based websites such as The New York Times and Source forge. I was wondering if you could apply this to websites where payment is a huge issue. I am thinking of the following issues: How well can you secure the data Do these system provide an easy backup/restore machanism How are transactions handled commit/rollback I have read the following articles that cover some aspects: Can I do transactions and locks in CouchDB? Pros/Cons of document based database vs relational database In these posts the aspect of transactions if covered. However the questions of security and backups is not covered. Can someone shed some light on this subject? And if possible, does anyone know of some e-commerce websites that have successfully implemented the document based database.

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  • NoSQL or Ehcache caching ?

    - by paddydub
    I'm building a Route Planner Webapp using Spring/Hibernate/Tomcat and a mysql database, I have a database containing read only data, such as Bus Stop Coordinates, Bus times which is never updated. I'm trying to make the app run faster, each time the application is run it will preform approx 1000 reads to the database to calculate a route. I have setup a Ehcache which greatly improves the read from database times. I'm now setting terracotta + Ehcache distributed caching to share the cache with multiple Tomcat JVMs. This seems a bit complicated. I've tried memcached but it was not performing as fast as ehcache. I'm wondering if a MongoDb or Redis would be better suited. I have no experience with nosql but I would appreciate if anyone has any ideas. What i need is quick access to the read only database.

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  • NoSQL replacement for memcache

    - by Juan Antonio Gomez Moriano
    We are having a situation in which the values we store on memcache are bigger than 1MB. It is not possible to make such values smaller, and even if there was a way, we need to persist them to disk. One solution would be to recompile the memcache server to allow say 2MB values, but this is either not clean nor a complete solution (again, we need to persist the values). Good news is that We can predict quite acurately how many key/values pair we are going to have We can also predict the total size we will need. A key feature for us is the speed of memcache. So question is: is there any noSQL replacement for memcache which will allow us to have values longer than 1MB AND store them in disk without loss of speed? In the past I have used tokyotyrant/cabinet but seems to be deprecated now. Any idea?

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  • Understanding NoSQL Data Modeling - blog application

    - by Rushabh RajeshKumar Padalia
    I am creating an blogging application in Node.js + MongoDB Database. I have used relational Database like MySQL before but this is my first experience with NoSQL database. So I would like to conform my MongoDB data models before I move further. I have decided my blogDB to have 3 collections post_collection - stores information about that article comment_collection - store information about comments on articles user_info_collection - contains user inforamtion PostDB { _"id" : ObjectID(...), "author": "author_name", "Date": new Date(....), "tag" : ["politics" , "war"], "post_title": "My first Article", "post_content": "Big big article" "likes": 23 "access": "public" } CommentDB { "_id" : Objectid(...), "POST": "My First Article", "comment_by": "User_name", "comment": "MY comments" } UserInfoDB { "_id": ObjectID(...), "user": "User_name", "password": "My_password" } I would appreciate your comments.

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  • What are good NoSQL and non-relational database solutions for audit/logging database

    - by Juha Syrjälä
    What would be suitable database for following? I am especially interested about your experiences with non-relational NoSQL systems. Are they any good for this kind of usage, which system you have used and would recommend, or should I go with normal relational database (DB2)? I need to gather audit trail/logging type information from bunch of sources to a centralized server where I could generate reports efficiently and examine what is happening in the system. Typically a audit/logging event would consist always of some mandatory fields, for example globally unique id (some how generated by program that generated this event) timestamp event type (i.e. user logged in, error happened etc) some information about source (server1, server2) Additionally the event could contain 0-N key-value pairs, where value might be up to few kilobytes of text. It must run on Linux server It should work with high amount of data (100GB for example) it should support some kind of efficient full text search It should allow concurrent reading and writing It should be flexible to add new event types and add/remove key-value pairs to new events. Flexible=no changes should be required to database schema, application generating the events can just add new event types/new fields as needed. it should be efficient to make queries against database. For reporting and exploring what happened. For example: How many events with type=X occurred in some time period. Get all events where field A has value Y. Get all events with type X and field A has value 1 and field B is not 2 and event occurred in last 24h

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  • File Storage for Web Applications: Filesystem vs DB vs NoSQL engines

    - by El Yobo
    I have a web application that stores a lot of user generated files. Currently these are all stored on the server filesystem, which has several downsides for me. When we move "folders" (as defined by our application) we also have to move the files on disk (although this is more due to strange design decisions on the part of the original developers than a requirement of storing things on the filesystem). It's hard to write tests for file system actions; I have a mock filesystem class that logs actions like move, delete etc, without performing them, which more or less does the job, but I don't have 100% confidence in the tests. I will be adding some other jobs which need to access the files from other service to perform additional tasks (e.g. indexing in Solr, generating thumbnails, movie format conversion), so I need to get at the files remotely. Doing this over network shares seems dodgy... Dealing with permissions on the filesystem as sometimes given us problems in the past, although now that we've moved to a pure Linux environment this should be less of an issue. What are the downsides of storing files as BLOBs in MySQL? I guess that it would massively increase the database size and reduce the effectiveness of caches, but are there other problems? Do the same problems exist with NoSQL systems like Cassandra? Does anyone have any other suggestions that might be appropriate?

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  • CouchOne et Membase fusionnent pour créer « Couchbase » et une famille de produits NoSQL de nouvelle génération

    CouchOne et Membase fusionnent pour créer « Couchbase » Et une famille de produits NoSQL de nouvelle génération Le paysage des solutions NoSQL est en pleine mutation depuis l'annonce de la première grande fusion de ce secteur, désormais très prospère et concurrentiel. Les deux entreprises CouchOne et Membase viennent de fusionner et d'annoncer la consolidation de leurs efforts pour la création de « Couchbase », le « premier éditeur de solution exhaustive de base de données NoSQL ». Sur son site officiel, CouchOne promet des possibilités de scalabilité sans précédent pour les produits qui vont résulter de cette fusion, pouvant propulser des « datacenter de la taille ...

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  • NoSQL Memcached API for MySQL: Latest Updates

    - by Mat Keep
    With data volumes exploding, it is vital to be able to ingest and query data at high speed. For this reason, MySQL has implemented NoSQL interfaces directly to the InnoDB and MySQL Cluster (NDB) storage engines, which bypass the SQL layer completely. Without SQL parsing and optimization, Key-Value data can be written directly to MySQL tables up to 9x faster, while maintaining ACID guarantees. In addition, users can continue to run complex queries with SQL across the same data set, providing real-time analytics to the business or anonymizing sensitive data before loading to big data platforms such as Hadoop, while still maintaining all of the advantages of their existing relational database infrastructure. This and more is discussed in the latest Guide to MySQL and NoSQL where you can learn more about using the APIs to scale new generations of web, cloud, mobile and social applications on the world's most widely deployed open source database The native Memcached API is part of the MySQL 5.6 Release Candidate, and is already available in the GA release of MySQL Cluster. By using the ubiquitous Memcached API for writing and reading data, developers can preserve their investments in Memcached infrastructure by re-using existing Memcached clients, while also eliminating the need for application changes. Speed, when combined with flexibility, is essential in the world of growing data volumes and variability. Complementing NoSQL access, support for on-line DDL (Data Definition Language) operations in MySQL 5.6 and MySQL Cluster enables DevOps teams to dynamically update their database schema to accommodate rapidly changing requirements, such as the need to capture additional data generated by their applications. These changes can be made without database downtime. Using the Memcached interface, developers do not need to define a schema at all when using MySQL Cluster. Lets look a little more closely at the Memcached implementations for both InnoDB and MySQL Cluster. Memcached Implementation for InnoDB The Memcached API for InnoDB is previewed as part of the MySQL 5.6 Release Candidate. As illustrated in the following figure, Memcached for InnoDB is implemented via a Memcached daemon plug-in to the mysqld process, with the Memcached protocol mapped to the native InnoDB API. Figure 1: Memcached API Implementation for InnoDB With the Memcached daemon running in the same process space, users get very low latency access to their data while also leveraging the scalability enhancements delivered with InnoDB and a simple deployment and management model. Multiple web / application servers can remotely access the Memcached / InnoDB server to get direct access to a shared data set. With simultaneous SQL access, users can maintain all the advanced functionality offered by InnoDB including support for Foreign Keys, XA transactions and complex JOIN operations. Benchmarks demonstrate that the NoSQL Memcached API for InnoDB delivers up to 9x higher performance than the SQL interface when inserting new key/value pairs, with a single low-end commodity server supporting nearly 70,000 Transactions per Second. Figure 2: Over 9x Faster INSERT Operations The delivered performance demonstrates MySQL with the native Memcached NoSQL interface is well suited for high-speed inserts with the added assurance of transactional guarantees. You can check out the latest Memcached / InnoDB developments and benchmarks here You can learn how to configure the Memcached API for InnoDB here Memcached Implementation for MySQL Cluster Memcached API support for MySQL Cluster was introduced with General Availability (GA) of the 7.2 release, and joins an extensive range of NoSQL interfaces that are already available for MySQL Cluster Like Memcached, MySQL Cluster provides a distributed hash table with in-memory performance. MySQL Cluster extends Memcached functionality by adding support for write-intensive workloads, a full relational model with ACID compliance (including persistence), rich query support, auto-sharding and 99.999% availability, with extensive management and monitoring capabilities. All writes are committed directly to MySQL Cluster, eliminating cache invalidation and the overhead of data consistency checking to ensure complete synchronization between the database and cache. Figure 3: Memcached API Implementation with MySQL Cluster Implementation is simple: 1. The application sends reads and writes to the Memcached process (using the standard Memcached API). 2. This invokes the Memcached Driver for NDB (which is part of the same process) 3. The NDB API is called, providing for very quick access to the data held in MySQL Cluster’s data nodes. The solution has been designed to be very flexible, allowing the application architect to find a configuration that best fits their needs. It is possible to co-locate the Memcached API in either the data nodes or application nodes, or alternatively within a dedicated Memcached layer. The benefit of this flexible approach to deployment is that users can configure behavior on a per-key-prefix basis (through tables in MySQL Cluster) and the application doesn’t have to care – it just uses the Memcached API and relies on the software to store data in the right place(s) and to keep everything synchronized. Using Memcached for Schema-less Data By default, every Key / Value is written to the same table with each Key / Value pair stored in a single row – thus allowing schema-less data storage. Alternatively, the developer can define a key-prefix so that each value is linked to a pre-defined column in a specific table. Of course if the application needs to access the same data through SQL then developers can map key prefixes to existing table columns, enabling Memcached access to schema-structured data already stored in MySQL Cluster. Conclusion Download the Guide to MySQL and NoSQL to learn more about NoSQL APIs and how you can use them to scale new generations of web, cloud, mobile and social applications on the world's most widely deployed open source database See how to build a social app with MySQL Cluster and the Memcached API from our on-demand webinar or take a look at the docs Don't hesitate to use the comments section below for any questions you may have 

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  • Guide to MySQL & NoSQL, Webinar Q&A

    - by Mat Keep
    0 0 1 959 5469 Homework 45 12 6416 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful. Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar. Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL: - On-Demand webinar (coming soon!) - Slides used during the webinar - Guide to MySQL and NoSQL whitepaper  - MySQL Cluster demo, including NoSQL interfaces, auto-sharing, high availability, etc.  So here is the Q&A from the event  Q. Where does MySQL Cluster fit in to the CAP theorem? A. MySQL Cluster is flexible. A single Cluster will prefer consistency over availability in the presence of network partitions. A pair of Clusters can be configured to prefer availability over consistency. A full explanation can be found on the MySQL Cluster & CAP Theorem blog post.  Q. Can you configure the number of replicas? (the slide used a replication factor of 1) Yes. A cluster is configured by an .ini file. The option NoOfReplicas sets the number of originals and replicas: 1 = no data redundancy, 2 = one copy etc. Usually there's no benefit in setting it >2. Q. Interestingly most (if not all) of the NoSQL databases recommend having 3 copies of data (the replication factor).    Yes, with configurable quorum based Reads and writes. MySQL Cluster does not need a quorum of replicas online to provide service. Systems that require a quorum need > 2 replicas to be able to tolerate a single failure. Additionally, many NoSQL systems take liberal inspiration from the original GFS paper which described a 3 replica configuration. MySQL Cluster avoids the need for a quorum by using a lightweight arbitrator. You can configure more than 2 replicas, but this is a tradeoff between incrementally improved availability, and linearly increased cost. Q. Can you have cross node group JOINS? Wouldn't that run into the risk of flooding the network? MySQL Cluster 7.2 supports cross nodegroup joins. A full cross-join can require a large amount of data transfer, which may bottleneck on network bandwidth. However, for more selective joins, typically seen with OLTP and light analytic applications, cross node-group joins give a great performance boost and network bandwidth saving over having the MySQL Server perform the join. Q. Are the details of the benchmark available anywhere? According to my calculations it results in approx. 350k ops/sec per processor which is the largest number I've seen lately The details are linked from Mikael Ronstrom's blog The benchmark uses a benchmarking tool we call flexAsynch which runs parallel asynchronous transactions. It involved 100 byte reads, of 25 columns each. Regarding the per-processor ops/s, MySQL Cluster is particularly efficient in terms of throughput/node. It uses lock-free minimal copy message passing internally, and maximizes ID cache reuse. Note also that these are in-memory tables, there is no need to read anything from disk. Q. Is access control (like table) planned to be supported for NoSQL access mode? Currently we have not seen much need for full SQL-like access control (which has always been overkill for web apps and telco apps). So we have no plans, though especially with memcached it is certainly possible to turn-on connection-level access control. But specifically table level controls are not planned. Q. How is the performance of memcached APi with MySQL against memcached+MySQL or any other Object Cache like Ecache with MySQL DB? With the memcache API we generally see a memcached response in less than 1 ms. and a small cluster with one memcached server can handle tens of thousands of operations per second. Q. Can .NET can access MemcachedAPI? Yes, just use a .Net memcache client such as the enyim or BeIT memcache libraries. Q. Is the row level locking applicable when you update a column through memcached API? An update that comes through memcached uses a row lock and then releases it immediately. Memcached operations like "INCREMENT" are actually pushed down to the data nodes. In most cases the locks are not even held long enough for a network round trip. Q. Has anyone published an example using something like PHP? I am assuming that you just use the PHP memcached extension to hook into the memcached API. Is that correct? Not that I'm aware of but absolutely you can use it with php or any of the other drivers Q. For beginner we need more examples. Take a look here for a fully worked example Q. Can I access MySQL using Cobol (Open Cobol) or C and if so where can I find the coding libraries etc? A. There is a cobol implementation that works well with MySQL, but I do not think it is Open Cobol. Also there is a MySQL C client library that is a standard part of every mysql distribution Q. Is there a place to go to find help when testing and/implementing the NoSQL access? If using Cluster then you can use the [email protected] alias or post on the MySQL Cluster forum Q. Are there any white papers on this?  Yes - there is more detail in the MySQL Guide to NoSQL whitepaper If you have further questions, please don’t hesitate to use the comments below!

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  • How should calculations be handled in a document database

    - by Morten
    Ok, so I have a program that basically logs errors into a nosql database. Right now there is just a single model for an error and its stored as a document in the nosql database. Basically I want to summarize across different errors and produce a summary of the "types" of errors that occured. Traditionally in a SQL database the this normalization would work with groupings, sums and averages but in a NoSQL database I assume I need to use mapreduce. My current model seems unfit for the task, how should I change the way I store "models" in order to make statistical analysis easy? Would a NoSQL database even be the right tool for this type of problem? I'm storing things in Google AppEngine's BigTable, so there are some limitations to think of as well.

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