Key-Value Stores: RiakKV
|
|
- Sharleen Wilson
- 5 years ago
- Views:
Transcription
1 B4M36DS2, BE4M36DS2: Database Systems 2 h p:// Lecture 7 Key-Value Stores: RiakKV Mar n Svoboda mar n.svoboda@fel.cvut.cz Charles University, Faculty of Mathema cs and Physics Czech Technical University in Prague, Faculty of Electrical Engineering
2 Lecture Outline Key-value stores Introduc on RiakKV Data model HTTP interface CRUD opera ons Links and Link walking Data types Search 2.0 Internal details B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
3 Key-Value Stores Data model The most simple NoSQL database type Works as a simple hash table (mapping) Key-value pairs Key (id, iden er, primary key) Value: binary object, black box for the database system Query pa erns Create, update or remove value for a given key Get value for a given key Characteris cs Simple model great performance, easily scaled, Simple model not for complex queries nor complex data B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
4 Key Management How the keys should actually be designed? Real-world iden ers E.g. addresses, login names, Automa cally generated values Auto-increment integers Not suitable in peer-to-peer architectures! Complex keys Mul ple components / combina ons of me stamps, cluster node iden ers, Used in prac ce instead Pre xes describing en ty types are o en used as well E.g.,, B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
5 Query Pa erns Basic CRUD opera ons Only when a key is provided knowledge of the keys is essen al It might even be di cult for a par cular database system to provide a list of all the available keys! Accessing the contents of the value part is not possible in general But we could instruct the database how to parse the values so that we can index them based on certain search criteria Batch / sequen al processing MapReduce B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
6 Other Func onality Expira on of key-value pairs Objects are automa cally removed from the database a er a certain interval of me Useful for user sessions, shopping carts etc. Links between key-value pairs Values can be mutually interconnected via links These links can be traversed when querying Collec ons of values Not only ordinary values can be stored, but also their collec ons (e.g. ordered lists, unordered sets, ) Par cular func onality always depends on the store we use! B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
7 Riak Key-Value Store
8 RiakKV Key-value store h p://basho.com/products/riak-kv/ Features Open source, incremental scalability, high availability, opera onal simplicity, decentralized design, automa c data distribu on, advanced replica on, fault tolerance, Developed by Basho Technologies Implemented in Erlang General-purpose, concurrent, garbage-collected programming language and run me system Opera ng system: Linux, Mac OS X, (not Windows) Ini al release in 2009 B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
9 Data Model Riak database system structure Instance ( bucket types) buckets objects Bucket = collec on of objects (logical, not physical collec on) Various proper es are set at the level of buckets E.g. default replica on factor, read / write quora, Object = key-value pair Key is a Unicode string Unique within a bucket Value can be anything (text, binary object, image, ) Each object is also associated with metadata E.g. its content type (,, ), and other internal metadata as well B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
10 Data Model Design Ques ons How buckets and objects should be modeled? Buckets with objects of a single en ty type E.g. one bucket for actors, one for movies, each actor and movie has its own object Buckets with objects of various en ty types E.g. one bucket for both actors and movies, each actor and movie has its own object once again Structured keys might then help E.g., Buckets with complex objects containing various data E.g. one object for all the actors, one for all the movies B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
11 Riak Usage: Querying Basic CRUD opera ons Create, Read, Update, and Delete Based on a key look-up Extended func onality Links rela onships between objects and their traversal Search 2.0 full-text queries accessing values of objects MapReduce B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
12 Riak Usage: API Applica on interfaces HTTP API All the user requests are submi ed as HTTP requests with appropriately selected / constructed methods, URLs, headers, and data Protocol Bu ers API Erlang API Client libraries for a variety of programming languages O cial: Java, Ruby, Python, C#, PHP, Community: C, C++, Haskell, Perl, Python, Scala, B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
13 Riak Usage: HTTP API curl tool Allows to transfer data from / to a server using HTTP (or other supported protocols) Op ons, HTTP request method to be used (GET, ), Data to be sent to the server (implies the POST method), Extra headers to be included when sending the request, Prints both headers and (not just) body of a response B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
14 Basic Opera ons
15 CRUD Opera ons Basic opera ons on objects Create: or methods Inserts a key-value pair into a given bucket Key is speci ed manually, or will be generated automa cally Read: method Retrieves a key-value pair from a given bucket Update: method Updates a key-value pair in a given bucket Delete: method Removes a key-value pair from a given bucket B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
16 CRUD Opera ons URL pa ern of HTTP requests for all the CRUD opera ons / buckets / bucket / keys / key? parameter = value & Op onal parameters (depending on the opera on), : read / write quorum to be a ained B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
17 CRUD Opera ons Create and Update Inserts / updates a key-value pair in a given bucket PUT method Should be used when a key is speci ed explicitly Transparently inserts / updates (replaces) a given object POST method When a key is to be generated automa cally Always inserts a new object Buckets are created transparently whenever needed Example B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
18 CRUD Opera ons Read Retrieves a key-value pair from a given bucket Method: GET Example Request Response B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
19 CRUD Opera ons Delete Removes a key-value pair from a given bucket Method: DELETE If a given object does not exist, it does not ma er Example B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
20 Bucket Opera ons Lists all the buckets (buckets with at least one object) / buckets? buckets = true B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
21 Bucket Opera ons Lists all the keys within a given bucket Not recommended to be used in produc on environments since it is a very expensive opera on / buckets / bucket / keys? keys = true B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
22 Bucket Opera ons Se ng and retrieval of bucket proper es Proper es : replica on factor,, : read / write quora and their alterna ves Requests GET / PUT method: retrieve / set bucket proper es / buckets / bucket / props Example B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
23 Links and Link Walking
24 Links and Link Walking Links Links are metadata that establish one-way rela onships between pairs of objects Act as lightweight pointers between individual key-value pairs I.e. represent and extension to the pure key-value data model Each link is de ned within the source object is associated with a tag (sort of link type) can be traversed in a given direc on only may connect objects even from di erent buckets Mul ple links can lead from / to a given object Link walking New way of querying naviga on between objects using links B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
25 Links How are links de ned? Special header is used for this purpose Mul ple link headers can be provided, or equivalently mul ple links within one header Link : < target > ; riaktag = " tag ", Example B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
26 Link Walking How can links be traversed? Standard GET requests with link traversal descrip on Exactly one object where the traversal is ini ated Accessed in a standard way Single or mul ple naviga onal steps then follow / buckets / bucket / keys / key / bucket _, tag _, 1 0 _ / B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
27 Link Walking Parameters of naviga on steps Only objects from a certain target bucket are selected when not limited to any par cular bucket Only links of a given tag are considered when not limited to any par cular tag when the discovered objects should be included in the result otherwise means for the very last step, for all the other preceding B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
28 Link Walking Examples Actors who played in Medvídek movie Movies in which appeared actors from Medvídek movie (assuming that the corresponding actor movie links also exist) B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
29 Data Types
30 Data Types Mo va on Riak began as a pure key-value store I.e. was completely agnos c toward the contents of values However, if availability is preferred to consistency, mutually con ic ng replicas might exist Such con icts can be resolved at the applica on level, but this is o en (only too) di cult for the developers And so the concept of Riak Data Types was introduced When used (it is not compulsory), Riak is able to resolve con icts automa cally B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
31 Data Types Convergent Replicated Data Types (CRDT) Generic concept Various types for several common scenarios Speci c con ict resolu on rules (convergence rules) Available data types Register, ag Can only be used embedded in maps Counter, set, and map Can be used embedded in maps as well as directly at the bucket level B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
32 Data Types Register Flag Allows to store any binary value (e.g. string, ) Convergence rule: the most chronologically recent value wins Boolean values: (true), and (false) Convergence rule: enable wins over disable Counter Opera ons: increment / decrement by a given integer value Convergence rule: all requested increments and decrements are eventually applied B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
33 Data Types Set Map Collec on of unique binary values Opera ons: addi on / removal of one / mul ple elements Convergence rule: addi on wins over removal of elements Collec on of elds with embedded elements of any data type (including other nested maps) Opera ons: addi on / removal of an element Convergence rule: addi on / update wins over removal B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
34 Search 2.0
35 Search 2.0 Riak Search 2.0 (Yokozuna) Full-text search over object values Uses Apache Solr Distributed, scalable, failure tolerant, real- me search pla orm How does it work? Indexa on Riak object extractor Solr document schema Solr index Querying Riak search query Solr search query Solr response: list of bucket-key pairs Riak response: list of objects B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
36 Search 2.0: Extractors Extractor Parses the object value and produces elds to be indexed Chosen automa cally based on a MIME type Available extractors Common prede ned extractors Plain text, XML, JSON, noop (unknown content type) Built-in extractors for Riak Data Types Counter, map, set User-de ned custom extractors Implemented in Erlang, registered with Riak B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
37 Search 2.0: Extractors Plain text extractor ( ) Single eld with the whole content is extracted Example Input Riak object Output Solr document B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
38 Search 2.0: Extractors XML extractor (, ) One eld is created for each element and a ribute Only elds with type su xes are considered E.g. for string, for integer, for boolean, Dot nota on is used to compose a en names of nested items Example Input Riak object / Output Solr document B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
39 Search 2.0: Extractors JSON extractor ( ) Similar principles as for XML documents are applied Example Input Riak object Output Solr document B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
40 Search 2.0: Indexa on Solr document Automa cally extracted elds + a few auxiliary elds such as: (bucket name), (key), Solr schema Describes how elds are indexed within Solr Values of elds are analyzed and split into terms Terms are normalized, stop words removed Triples (token, eld, document) are produced and indexed Default schema available ( ) Suitable for debugging, but custom schemas should be used in produc on B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
41 Search 2.0: Index Crea on How is index created? Index must be created rst, then associated with a single bucket Example B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
42 Search 2.0: Index Usage Search queries Parameters search query (correctly encoded) Individual search criteria response write Query result format / pagina on of matching objects / search / query / index? parameter = value & B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
43 Search 2.0: Index Usage Available search func onality Wildcards E.g., Range queries E.g. Logical connec ves and parentheses,, Proximity searches B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
44 Internal Details
45 Architecture Sharding + peer-to-peer replica on architecture Any node can serve any read or write user request Physical nodes run (several) virtual nodes (vnodes) Nodes can be added and removed from the cluster dynamically Gossip protocol Each node periodically sends its current view of the cluster, its state and changes, bucket proper es, CAP proper es AP system: availability + par on tolerance B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
46 Consistency BASE principles Availability is preferred to consistency Default proper es of buckets : replica on factor : read quorum : write quorum (node par cipa on is su cient) : write quorum (write to durable storage is required) Speci c op ons of requests override the bucket proper es Strong consistency can be achieved When quora set carefully, i.e.: > _ / for write quorum > _ for read quorum B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
47 Causal Context Con ic ng replicas are unavoidable (with eventual consistency) how are they resolved? Causal context = auxiliary data and mechanisms that are necessary in order to resolve the con icts Low-level techniques Timestamps, vectors clocks, do ed version vectors They can be used to resolve con icts automa cally Might fail, then we must make the choice by ourselves Or we can resolve the con icts manually Siblings then need to be enabled ( ) = mul ple versions of object values User-friendly CRDT data types with built in resolu on Register, ag, counter, set, map B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
48 Causal Context Vector clocks Mechanism for tracking object update causality in terms of logical me (not chronological me) Each node has its own logical clock (integer counter) Ini ally equal to 0 Incremented by 1 whenever any event takes place Vector clock = vector of logical clocks of all the nodes Each node maintains its local copy of this vector Whenever a message is sent, the local vector is sent as well Whenever a message is received, the local vector is updated Maximal value for each individual node clock is taken B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
49 Vector Clocks B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
50 Vector Clocks B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
51 Vector Clocks B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
52 Vector Clocks B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
53 Vector Clocks B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
54 Vector Clocks B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
55 Riak Ring Replica placement strategy Consistent hashing func on Consistent = does not change when cluster changes Domain: pairs of a bucket name and object key Range: 160-bit integer space = Riak Ring Riak Ring The whole ring is split into equally-sized disjoint par ons Physical nodes are mutually interleaved reshu ing when cluster changes is less demanding Each virtual node is responsible for exactly one par on Example Cluster with 4 physical nodes, each running 8 virtual nodes I.e. 32 par ons altogether B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
56 Riak Ring Source: h p://docs.basho.com/ B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
57 Riak Ring Replica placement strategy The rst replica Its loca on is directly determined by the hash func on All the remaining replicas Placed to the consecu ve par ons in a clockwise direc on What if a virtual node is failing? Hinted hando Failing nodes are simply skipped, neighboring nodes temporarily take responsibility When resolved, replicas are handed o to the proper loca ons Mo va on: high availability B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
58 Request Handling Read and write requests can be submi ed to any node This nodes is called a coordina ng node Hash func on is calculated, i.e. replica loca ons determined Internal requests are sent to all the corresponding nodes Then the coordina ng node waits un l su cient number of responses is received Result / failure is returned to the user But what if the cluster changes? The value of the hash func on does not change, only the par ons and their mapping to virtual nodes change However, the Ring knowledge a given node has might be obsolete! B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
59
60 Lecture Conclusion RiakKV Highly available distributed key-value store Sharding with peer-to-peer replica on architecture Riak Ring with consistent hashing for replica placement Query func onality Basic CRUD opera ons Link walking Search 2.0 full-text based on Apache Solr B4M36DS2, BE4M36DS2: Database Systems 2 Lecture 7: Key-Value Stores: RiakKV
Key-Value Stores: RiakKV
B4M36DS2: Database Systems 2 h p://www.ksi.mff.cuni.cz/ svoboda/courses/2016-1-b4m36ds2/ Lecture 4 Key-Value Stores: RiakKV Mar n Svoboda svoboda@ksi.mff.cuni.cz 24. 10. 2016 Charles University in Prague,
More informationKey-Value Stores: RiakKV
NDBI040: Big Data Management and NoSQL Databases h p://www.ksi.mff.cuni.cz/ svoboda/courses/2016-1-ndbi040/ Lecture 4 Key-Value Stores: RiakKV Mar n Svoboda svoboda@ksi.mff.cuni.cz 25. 10. 2016 Charles
More informationNDBI040: Big Data Management and NoSQL Databases. h p:// svoboda/courses/ ndbi040/
NDBI040: Big Data Management and NoSQL Databases h p://www.ksi.mff.cuni.cz/ svoboda/courses/2016-1-ndbi040/ Prac cal Class 2 Riak Key-Value Store Mar n Svoboda svoboda@ksi.mff.cuni.cz 25. 10. 2016 Charles
More informationNDBI040: Big Data Management and NoSQL Databases. h p://
NDBI040: Big Data Management and NoSQL Databases h p://www.ksi.mff.cuni.cz/~svoboda/courses/171-ndbi040/ Prac cal Class 5 Riak Mar n Svoboda svoboda@ksi.mff.cuni.cz 13. 11. 2017 Charles University in Prague,
More informationB4M36DS2, BE4M36DS2: Database Systems 2
B4M36DS2, BE4M36DS2: Database Systems 2 h p://www.ksi.mff.cuni.cz/~svoboda/courses/171-b4m36ds2/ Lecture 2 Data Formats Mar n Svoboda mar n.svoboda@fel.cvut.cz 9. 10. 2017 Charles University in Prague,
More informationh p://
B4M36DS2, BE4M36DS2: Database Systems 2 h p://www.ksi.m.cuni.cz/~svoboda/courses/181-b4m36ds2/ Prac cal Class 7 Redis Mar n Svoboda mar n.svoboda@fel.cvut.cz 19. 11. 2018 Charles University, Faculty of
More informationColumn-Family Stores: Cassandra
NDBI040: Big Data Management and NoSQL Databases h p://www.ksi.mff.cuni.cz/ svoboda/courses/2016-1-ndbi040/ Lecture 10 Column-Family Stores: Cassandra Mar n Svoboda svoboda@ksi.mff.cuni.cz 13. 12. 2016
More informationNDBI040: Big Data Management and NoSQL Databases
NDBI040: Big Data Management and NoSQL Databases h p://www.ksi.mff.cuni.cz/~svoboda/courses/171-ndbi040/ Prac cal Class 8 MongoDB Mar n Svoboda svoboda@ksi.mff.cuni.cz 5. 12. 2017 Charles University in
More informationh p://
B4M36DS2, BE4M36DS2: Database Systems 2 h p://www.ksi.m.cuni.cz/~svoboda/courses/181-b4m36ds2/ Prac cal Class 5 MapReduce Mar n Svoboda mar n.svoboda@fel.cvut.cz 5. 11. 2018 Charles University, Faculty
More informationMapReduce, Apache Hadoop
B4M36DS2, BE4M36DS2: Database Systems 2 h p://www.ksi.mff.cuni.cz/~svoboda/courses/171-b4m36ds2/ Lecture 5 MapReduce, Apache Hadoop Mar n Svoboda mar n.svoboda@fel.cvut.cz 30. 10. 2017 Charles University
More informationh p://
B4M36DS2, BE4M36DS2: Database Systems 2 h p://www.ksi.mff.cuni.cz/~svoboda/courses/171-b4m36ds2/ Prac cal Class 7 Cassandra Mar n Svoboda mar n.svoboda@fel.cvut.cz 27. 11. 2017 Charles University in Prague,
More informationRiak. Distributed, replicated, highly available
INTRO TO RIAK Riak Overview Riak Distributed Riak Distributed, replicated, highly available Riak Distributed, highly available, eventually consistent Riak Distributed, highly available, eventually consistent,
More informationh p://
B4M36DS2, BE4M36DS2: Database Systems 2 h p://www.ksi.mff.cuni.cz/~svoboda/courses/171-b4m36ds2/ Lecture 1 Introduc on Mar n Svoboda mar n.svoboda@fel.cvut.cz 2. 10. 2017 Charles University in Prague,
More informationB0B36DBS, BD6B36DBS: Database Systems
B0B36DBS, BD6B36DBS: Database Systems h p://www.ksi.m.cuni.cz/~svoboda/courses/172-b0b36dbs/ Prac cal Class 10 JDBC, JPA 2.1 Author: Mar n Svoboda, mar n.svoboda@fel.cvut.cz Tutors: J. Ahmad, R. Černoch,
More informationAdvanced Databases ( CIS 6930) Fall Instructor: Dr. Markus Schneider. Group 17 Anirudh Sarma Bhaskara Sreeharsha Poluru Ameya Devbhankar
Advanced Databases ( CIS 6930) Fall 2016 Instructor: Dr. Markus Schneider Group 17 Anirudh Sarma Bhaskara Sreeharsha Poluru Ameya Devbhankar BEFORE WE BEGIN NOSQL : It is mechanism for storage & retrieval
More informationDocument Databases: MongoDB
NDBI040: Big Data Management and NoSQL Databases hp://www.ksi.mff.cuni.cz/~svoboda/courses/171-ndbi040/ Lecture 9 Document Databases: MongoDB Marn Svoboda svoboda@ksi.mff.cuni.cz 28. 11. 2017 Charles University
More information#IoT #BigData. 10/31/14
#IoT #BigData Seema Jethani @seemaj @basho 1 10/31/14 Why should we care? 2 11/2/14 Source: http://en.wikipedia.org/wiki/internet_of_things Motivation for Specialized Big Data Systems Rate of data capture
More informationPutting together the platform: Riak, Redis, Solr and Spark. Bryan Hunt
Putting together the platform: Riak, Redis, Solr and Spark Bryan Hunt 1 $ whoami Bryan Hunt Client Services Engineer @binarytemple 2 Minimum viable product - the ideologically correct doctrine 1. Start
More informationREGION: NORTH AMERICA
R U M A REGION: NORTH AMERICA R U M A Chapter Issue Date 1 Introduc on 05/21/2012 2 Install and Upgrade Minimum Hardware Requirements Android Opera ng System and Wi Fi Se ngs Installing Revoquest the First
More informationDr. Chuck Cartledge. 14 Sept. 2015
CS-695 NoSQL Database Riak (part 2 of 2) Dr. Chuck Cartledge 14 Sept. 2015 1/21 Table of contents I 5 Summary 1 Miscellanea 2 Assignment #2 3 Extensions 4 Break 6 Conclusion 7 References 8 Backup slides
More informationHarnessing Publicly Available Factual Data in the Analytical Process
June 14, 2012 Harnessing Publicly Available Factual Data in the Analytical Process by Benson Margulies, CTO We put the World in the World Wide Web ABOUT BASIS TECHNOLOGY Basis Technology provides so ware
More informationDEMYSTIFYING BIG DATA WITH RIAK USE CASES. Martin Schneider Basho Technologies!
DEMYSTIFYING BIG DATA WITH RIAK USE CASES Martin Schneider Basho Technologies! Agenda Defining Big Data in Regards to Riak A Series of Trade-Offs Use Cases Q & A About Basho & Riak Basho Technologies is
More informationWhat am I? Bryan Hunt Basho Client Services Engineer Erlang neophyte JVM refugee Be gentle
What am I? Bryan Hunt Basho Client Services Engineer Erlang neophyte JVM refugee Be gentle What are you? Developer Operations Other Structure of this talk Introduction to Riak Introduction to Riak 2.0
More informationFrom Relational to Riak
www.basho.com From Relational to Riak December 2012 Table of Contents Table of Contents... 1 Introduction... 1 Why Migrate to Riak?... 1 The Requirement of High Availability...1 Minimizing the Cost of
More informationPresented By: Devarsh Patel
: Amazon s Highly Available Key-value Store Presented By: Devarsh Patel CS5204 Operating Systems 1 Introduction Amazon s e-commerce platform Requires performance, reliability and efficiency To support
More informationREST Services. Zaenal Akbar
PS/ Web Services REST Services Zaenal Akbar Friday, - - Outline REST Services Overview Principles Common Errors Exercise What is REST? Set of architectural principles used for design of distributed systems
More informationrelational Relational to Riak Why Move From Relational to Riak? Introduction High Availability Riak At-a-Glance
WHITEPAPER Relational to Riak relational Introduction This whitepaper looks at why companies choose Riak over a relational database. We focus specifically on availability, scalability, and the / data model.
More informationSelf-healing Data Step by Step
Self-healing Data Step by Step Uwe Friedrichsen (codecentric AG) NoSQL matters Cologne, 29. April 2014 @ufried Uwe Friedrichsen uwe.friedrichsen@codecentric.de http://slideshare.net/ufried http://ufried.tumblr.com
More informationDigital Analy 韜 cs Installa 韜 on and Configura 韜 on
Home > Digital AnalyĀcs > Digital Analy 韜 cs Installa 韜 on and Configura 韜 on Digital Analy 韜 cs Installa 韜 on and Configura 韜 on Introduc 韜 on Digital Analy 韜 cs is an e automate applica 韜 on that assists
More informationThe course modules of MongoDB developer and administrator online certification training:
The course modules of MongoDB developer and administrator online certification training: 1 An Overview of the Course Introduction to the course Table of Contents Course Objectives Course Overview Value
More informationCSE 544 Principles of Database Management Systems. Magdalena Balazinska Winter 2015 Lecture 14 NoSQL
CSE 544 Principles of Database Management Systems Magdalena Balazinska Winter 2015 Lecture 14 NoSQL References Scalable SQL and NoSQL Data Stores, Rick Cattell, SIGMOD Record, December 2010 (Vol. 39, No.
More informationDistributed Systems Exam 1 Review Paul Krzyzanowski. Rutgers University. Fall 2016
Distributed Systems 2015 Exam 1 Review Paul Krzyzanowski Rutgers University Fall 2016 1 Question 1 Why did the use of reference counting for remote objects prove to be impractical? Explain. It s not fault
More informationWEB TEACHER GUIDE. ebackpack provides a separate Student Guide through our support site at
ebackpack Web Teacher Guide Page 1 of 21 WEB TEACHER GUIDE This guide will cover basic usage of ebackpack for a teacher (assignments, storage, homework review, collaboration, and Act As support). If you
More informationDFM Concurrent Costing
Die Casting Analysis Start a new analysis For the purposes of this tutorial we will es mate the cost per part of manufacturing 200,000 of the disk drive casings shown here: front The material is to be
More informationCS Amazon Dynamo
CS 5450 Amazon Dynamo Amazon s Architecture Dynamo The platform for Amazon's e-commerce services: shopping chart, best seller list, produce catalog, promotional items etc. A highly available, distributed
More informationCourse Content MongoDB
Course Content MongoDB 1. Course introduction and mongodb Essentials (basics) 2. Introduction to NoSQL databases What is NoSQL? Why NoSQL? Difference Between RDBMS and NoSQL Databases Benefits of NoSQL
More informationOPTIONAL EXERCISE 1: CREATING A FUSION PROJECT PART A
Exercise Objec ves In the previous exercises, you were provided a full Fusion LIDAR dataset. In this exercise, you will begin with raw LIDAR data and create a new Fusion project one that will be as complete
More informationSpotify. Scaling storage to million of users world wide. Jimmy Mårdell October 14, 2014
Cassandra @ Spotify Scaling storage to million of users world wide! Jimmy Mårdell October 14, 2014 2 About me Jimmy Mårdell Tech Product Owner in the Cassandra team 4 years at Spotify
More informationBT SIP Trunk CRF User Guide - BT Sales / Originator + Specialist
BT SIP Trunk CRF User Guide - BT Sales / Originator + Specialist The following informa on provides an overview of how to use and complete the SIP Trunk elements of the BT System CRF portal. 1. Introduc
More informationDynamo: Amazon s Highly Available Key-Value Store
Dynamo: Amazon s Highly Available Key-Value Store DeCandia et al. Amazon.com Presented by Sushil CS 5204 1 Motivation A storage system that attains high availability, performance and durability Decentralized
More informationCIB Session 12th NoSQL Databases Structures
CIB Session 12th NoSQL Databases Structures By: Shahab Safaee & Morteza Zahedi Software Engineering PhD Email: safaee.shx@gmail.com, morteza.zahedi.a@gmail.com cibtrc.ir cibtrc cibtrc 2 Agenda What is
More informationQ. How do I start using Mānoa Guardian? A. Go to the App Store or Google Play on your mobile device and download the app. Search for Rave Guardian.
How it Works Q: Why use? A. is designed to allow users quick and easy contact with UH Mānoa Department of Public Safety (DPS) officers, and has addi onal features for increasing safety on campus. Using,
More informationBuyer s Guide. Contents. This guide will review how to shop, create requisi ons and track your requisi ons, orders and invoices
Buyer s Guide This guide will review how to shop, create requisi ons and track your requisi ons, orders and invoices Contents Buyer s Guide... 1 Logging In & Buyer s Role... 3 Key Concepts... 4 My Account
More informationWhat Came First? The Ordering of Events in
What Came First? The Ordering of Events in Systems @kavya719 kavya the design of concurrent systems Slack architecture on AWS systems with multiple independent actors. threads in a multithreaded program.
More informationPhysician Reference Guide Paragon Clinician Hub Version 13.0
Physician Reference Guide Paragon Clinician Hub Version 13.0 Table of Contents Table of Contents Clinician Hub 13.0 4 5 Clinician Hub 13.0 6 7 Key Features Clinician Hub 13.0 How to Unlock an Applica on
More informationDatabase Architectures
B0B36DBS, BD6B36DBS: Database Systems h p://www.ksi.m.cuni.cz/~svoboda/courses/172-b0b36dbs/ Lecture 11 Database Architectures Authors: Tomáš Skopal, Irena Holubová Lecturer: Mar n Svoboda, mar n.svoboda@fel.cvut.cz
More informationPermits User s Guide. Submit Application. Upload Files & Pay Fees. Plan Review Process. Final PreScreen. Project Approval. Electronic Plan Review
New Castle County Land Use Permits Sec on Electronic Plan Review Permits User s Guide Submit Application Upload Files & Pay Fees Plan Review Process Final PreScreen Project Approval Rev. 06/2018 2 l eplans
More informationCS 655 Advanced Topics in Distributed Systems
Presented by : Walid Budgaga CS 655 Advanced Topics in Distributed Systems Computer Science Department Colorado State University 1 Outline Problem Solution Approaches Comparison Conclusion 2 Problem 3
More informationSOLAR. User manual of high security level electronic lock. Gebaude Sicherheitstechnik Vertriebs GmbH, Kassel
SOLAR User manual of high security level electronic lock Gebaude Sicherheitstechnik Vertriebs GmbH, 34123 Kassel Wer. 1.1 / 02-2013 Contents General informa on...3 Func ons overview and descrip on...4
More informationSpecial Topic: Automated Report Recipients 5. Crea ng a New Region 6 Adding Districts to Regions 8
TT Tracker Set-up 3 Project Modifica ons 3 Access Country Project 3 Create Web Users 4 Special Topic: Automated Report Recipients 5 Create Program Loca ons (Coverage Areas) 6 Crea ng a New Region 6 Adding
More informationNetworking for Wide Format Printers
Networking for Wide Format Printers Table of Contents Configure PC before RIP Installa on... 1 Verifying Your Network Se ngs for Mac Communica on... 3 Changing Your Network Adapter for Mac Communica on...
More informationMyCouncil. Accredita on Management System Informa on and Naviga on Guide
MyCouncil Accredita on Management System Informa on and Naviga on Guide October 2017 MyCouncil GENERAL INFORMATION MyCouncil is a web based accredita on management system created to streamline accredita
More informationCanvas USSD Service Center Interac ve Services for a Mobile World. Copyright 2018 Telenity Confiden al & Proprietary
Canvas USSD Service Center Interac ve for a Mobile World Copyright 2018 Telenity Confiden al & Proprietary Canvas USSD Service Center Canvas USSD Service Center wireless operators to offer rapid and secure
More informationUnit 1 3 Dependency Injection & Inversion of Control
Unit 1 3 Dependency Injection & Inversion of Control This is a free chapter from our CBOX202: WireBox Dependency Injection course (www.coldbox.org/courses/cbox202) and is freely donated to the ColdFusion
More informationCAP Theorem, BASE & DynamoDB
Indian Institute of Science Bangalore, India भ रत य व ज ञ न स स थ न ब गल र, भ रत DS256:Jan18 (3:1) Department of Computational and Data Sciences CAP Theorem, BASE & DynamoDB Yogesh Simmhan Yogesh Simmhan
More informationCache Memories : Introduc on to Computer Systems 12 th Lecture, October 6th, Instructor: Randy Bryant.
Cache Memories 15-213: Introduc on to Computer Systems 12 th Lecture, October 6th, 2016 Instructor: Randy Bryant 1 Today Cache memory organiza on and opera on Performance impact of caches The memory mountain
More informationImage Crea)on MODULE 2. mpcdata delivering software innovation
Image Crea)on MODULE 2 Learning Objec-ves - Module 2 In this module we will learn about: Feature Sets and Packages Wizard based and advanced Image crea-on (IBW and ICE) Target Analyzer Introduc-on to Windows
More informationMicroso 埘 Exam Dumps PDF for Guaranteed Success
Microso 埘 70 698 Exam Dumps PDF for Guaranteed Success The PDF version is simply a copy of a Portable Document of your Microso 埘 70 698 ques ons and answers product. The Microso 埘 Cer fied Solu on Associa
More informationDIRECT SUPPLIER P RTAL INSTRUCTIONS
DIRECT SUPPLIER P RTAL INSTRUCTIONS page I IMPORTANT Please complete short Online Tutorials and Quiz at www.supplierportal.coles.com.au/dsd TABLE of Contents 1 Ingredients 2 Log In 3 View a Purchase Order
More informationDYNAMO: AMAZON S HIGHLY AVAILABLE KEY-VALUE STORE. Presented by Byungjin Jun
DYNAMO: AMAZON S HIGHLY AVAILABLE KEY-VALUE STORE Presented by Byungjin Jun 1 What is Dynamo for? Highly available key-value storages system Simple primary-key only interface Scalable and Reliable Tradeoff:
More informationSQL: Advanced Constructs
B0B36DBS, BD6B36DBS: Database Systems h p://www.ksi.mff.cuni.cz/~svoboda/courses/172-b0b36dbs/ Prac cal Class 8 SQL: Advanced Constructs Author: Mar n Svoboda, mar n.svoboda@fel.cvut.cz Tutors: J. Ahmad,
More informationIntroduction to NoSQL Databases
Introduction to NoSQL Databases Roman Kern KTI, TU Graz 2017-10-16 Roman Kern (KTI, TU Graz) Dbase2 2017-10-16 1 / 31 Introduction Intro Why NoSQL? Roman Kern (KTI, TU Graz) Dbase2 2017-10-16 2 / 31 Introduction
More informationelectronic license applications user s guide Contents What you need Page 1 Get started Page 3 Paper Non-Resident Licensing Page 10
applications Contents What you need Page 1 Get started Page 3 Paper Non-Resident Licensing Page 10 Welcome to the Na onal Insurance Producer Registry s applications The give producers the ability to quickly
More informationPERFORMANCE NAVIGATOR MANUAL
VERSION 19 MAY 21, 2018 PERFORMANCE NAVIGATOR MANUAL Proprietary Rights 2018 Midrange Performance Group, Inc. (MPG). All rights reserved. The informa on contained in this manual is subject to change at
More information1. Product descrip on copy
This document contains essen al marke ng copy for resellers, for use on product store, news announcements and technical documenta on. In this document: 1. Product descrip on copy 2. USP features (short)
More informationTANKLOGIX PORTAL TICKET MANAGEMENT 3.0 AUTHOR: GREG BAGLEY
TANKLOGIX PORTAL TICKET MANAGEMENT 3.0 AUTHOR: GREG BAGLEY CONTENTS INTRODUCTION... 3 PORTAL NAVIGATION... 3 Disposals > Ticket Management 3.0... 3 PAGE FEATURES... 3 TITLE AREA PAGE TOP... 4 SITES...
More informationTANKLOGIX PORTAL TICKET MANAGEMENT 3.2 AUTHOR: GREG BAGLEY
TANKLOGIX PORTAL TICKET MANAGEMENT 3.2 AUTHOR: GREG BAGLEY CONTENTS INTRODUCTION... 3 PORTAL NAVIGATION... 3 Disposals > Ticket Management 3.2... 3 PAGE FEATURES... 3 TITLE AREA PAGE TOP... 4 SITES...
More informationEECS 498 Introduction to Distributed Systems
EECS 498 Introduction to Distributed Systems Fall 2017 Harsha V. Madhyastha Dynamo Recap Consistent hashing 1-hop DHT enabled by gossip Execution of reads and writes Coordinated by first available successor
More informationImproving Logical Clocks in Riak with Dotted Version Vectors: A Case Study
Improving Logical Clocks in Riak with Dotted Version Vectors: A Case Study Ricardo Gonçalves Universidade do Minho, Braga, Portugal, tome@di.uminho.pt Abstract. Major web applications need the partition-tolerance
More informationThere is a tempta7on to say it is really used, it must be good
Notes from reviews Dynamo Evalua7on doesn t cover all design goals (e.g. incremental scalability, heterogeneity) Is it research? Complexity? How general? Dynamo Mo7va7on Normal database not the right fit
More informationIn Workflow. Viewing: Last edit: 11/04/14 4:01 pm. Approval Path. Programs referencing this course. Submi er: Proposing College/School: Department:
1 of 5 1/6/2015 1:20 PM Date Submi ed: 11/04/14 4:01 pm Viewing: Last edit: 11/04/14 4:01 pm Changes proposed by: SIMSLUA In Workflow 1. INSY Editor 2. INSY Chair 3. EN Undergraduate Curriculum Commi ee
More informationChapter 24 NOSQL Databases and Big Data Storage Systems
Chapter 24 NOSQL Databases and Big Data Storage Systems - Large amounts of data such as social media, Web links, user profiles, marketing and sales, posts and tweets, road maps, spatial data, email - NOSQL
More informationRiso Comcolor Series
Riso Comcolor Series Ge ng Started Guide No. 1 Ini al Setup Administrator Func ons Administrator Setup Default Se ngs User Names and Passwords Setup IC Card Control System Configura on Riso (UK) Limited
More informationSTM. Computing. Specifica on Topics. High Level Skills you should think about to take your work to the next level:
Specifica on Topics High Level Skills you should think about to take your work to the next level: Discussing the advantages and disadvantages of the different topology types Describing the key fields in
More informationCS 4604: Introduc0on to Database Management Systems. B. Aditya Prakash Lecture #7: En-ty/Rela-onal Model---Part 3
CS 4604: Introduc0on to Database Management Systems B. Aditya Prakash Lecture #7: En-ty/Rela-onal Model---Part 3 Purpose of E/R Model The E/R model allows us to sketch the design of a database informally.
More informationGeometric verifica-on of matching
Geometric verifica-on of matching The correspondence problem The correspondence problem tries to figure out which parts of an image correspond to which parts of another image, a;er the camera has moved,
More informationAccess Control Manager TM Release Notes
Access Control Manager TM 5.12.2 Release Notes Version 5.12.2 Released Monday, March 4, 2019 Files Released Avigilon Access Control Manager Physical Appliance Files 5.12.2.25-64 bit OS and Applica on Upgrade
More informationJargons, Concepts, Scope and Systems. Key Value Stores, Document Stores, Extensible Record Stores. Overview of different scalable relational systems
Jargons, Concepts, Scope and Systems Key Value Stores, Document Stores, Extensible Record Stores Overview of different scalable relational systems Examples of different Data stores Predictions, Comparisons
More informationSet Up Your Print. Overview. The main interface has five components: 1. 3D Viewer
Set Up Your Print Overview Open Uniz Desktop and click Control Bu on to show the 3D model viewer. The main interface has five components: 1. 3D Viewer https://uniz3d.com/support/supportsetprint/ 1/23 2.
More informationSearch Engines and Time Series Databases
Università degli Studi di Roma Tor Vergata Dipartimento di Ingegneria Civile e Ingegneria Informatica Search Engines and Time Series Databases Corso di Sistemi e Architetture per Big Data A.A. 2017/18
More informationReferences. NoSQL Motivation. Why NoSQL as the Solution? NoSQL Key Feature Decisions. CSE 444: Database Internals
References SE 444: atabase Internals Scalable SQL and NoSQL ata Stores, Rick attell, SIGMO Record, ecember 2010 (Vol. 39, No. 4) ynamo: mazon s Highly vailable Key-value Store. y Giuseppe eandia et. al.
More informationEventually Consistent HTTP with Statebox and Riak
Eventually Consistent HTTP with Statebox and Riak Author: Bob Ippolito (@etrepum) Date: November 2011 Venue: QCon San Francisco 2011 1/62 Introduction This talk isn't really about web. It's about how we
More informationDynamo. Smruti R. Sarangi. Department of Computer Science Indian Institute of Technology New Delhi, India. Motivation System Architecture Evaluation
Dynamo Smruti R. Sarangi Department of Computer Science Indian Institute of Technology New Delhi, India Smruti R. Sarangi Leader Election 1/20 Outline Motivation 1 Motivation 2 3 Smruti R. Sarangi Leader
More informationDistributed Systems. Pre-Exam 1 Review. Paul Krzyzanowski. Rutgers University. Fall 2015
Distributed Systems Pre-Exam 1 Review Paul Krzyzanowski Rutgers University Fall 2015 October 2, 2015 CS 417 - Paul Krzyzanowski 1 Selected Questions From Past Exams October 2, 2015 CS 417 - Paul Krzyzanowski
More informationRemote Ticket Entry. System/User Requirements
North Carolina 811, Inc. 2300 West Meadowview Rd Suite 227 Greensboro, North Carolina 27407 336.855.5760 Remote Ticket Entry An internet based cket entry system, Remote Ticket Entry (RTE), allows excavators
More informationVmware 2V0 641 Exam Dumps PDF for Guaranteed Success
Vmware 2V0 641 Exam Dumps PDF for Guaranteed Success The PDF version is simply a copy of a Portable Document of your Vmware 2V0 641 ques 韫 ons and answers product. The VMware Cer 韫 fied Professional 6
More informationJune 20, 2017 Revision NoSQL Database Architectural Comparison
June 20, 2017 Revision 0.07 NoSQL Database Architectural Comparison Table of Contents Executive Summary... 1 Introduction... 2 Cluster Topology... 4 Consistency Model... 6 Replication Strategy... 8 Failover
More informationSIRE Solution Suite. Better Outcomes. Active Review Administration and User Manual. A Publication Of
Active Review Administration and User Manual SIRE Solution Suite An Official Manual of SIRE Technologies Document and Legislative Management Software Version 6.3 A Publication Of Better Outcomes. 2 SIRE
More informationWhat is MyDtxt? 2 Why use MyDtxt? 2 Ge ng started and crea ng an account 2 How do I text my customers? 3. How do I get feedback from my customers?
TABLE OF CONTENTS What is MyDtxt? 2 Why use MyDtxt? 2 Ge ng started and crea ng an account 2 How do I text my customers? 3 Crea ng keywords Sending messages to your members How do I get feedback from my
More informationDynamo: Amazon s Highly Available Key-value Store
Dynamo: Amazon s Highly Available Key-value Store Giuseppe DeCandia, Deniz Hastorun, Madan Jampani, Gunavardhan Kakulapati, Avinash Lakshman, Alex Pilchin, Swaminathan Sivasubramanian, Peter Vosshall and
More informationAgile Test Data Management
ebook O V E R C O M I N G L I M I T S Agile Test Data Management - An Emerging Best Practice in Digital Economy Table of Contents Impact of Poorly Managed/Implemented Test Data... 4 Why Does Test Data
More informationRefWorks User Quick Start Guide VERSION 5.0
RefWorks User Quick Start Guide VERSION 5.0 LOGGING IN Access www.refworks.com/refworks and then enter your personal Login Name and Password. (First- me users need to sign up for an individual account
More informationJulia Eclipse Plugin User Manual Table of Contents
Julia Eclipse Plugin User Manual Table of Contents Introduction Installation Settings Running Julia Navigating the Results Managing analyses results Extraction of the application under analysis Julia Java
More informationWe are ready to serve Latest Testing Trends, Are you ready to learn?? New Batches Info
We are ready to serve Latest Testing Trends, Are you ready to learn?? New Batches Info START DATE : TIMINGS : DURATION : TYPE OF BATCH : FEE : FACULTY NAME : LAB TIMINGS : PH NO: 9963799240, 040-40025423
More informationPrinted Circuit Board Assembly Analysis / 1
Printed Circuit Board Assembly Analysis Introduction DFM Concurrent Costing The first step in the manufacture of the printed circuit board assembly is the fabrica on of the bare circuit board, o en called
More informationEXERCISE 2: GETTING STARTED WITH FUSION
Exercise Objec ves In this exercise, you ll be using the fully prepared example data to explore the basics of FUSION. Prerequisites Successful comple on of Exercise 1 (Download and Install FUSION and the
More informationJulia Eclipse Plugin User Manual. Version 2.6.0
Version 2.6.0 Table of Contents Introduction Installation Settings Running Julia Navigating the Results Managing analyses results Extraction of the application under analysis Julia Java Project Wizard
More informationCS 138: Dynamo. CS 138 XXIV 1 Copyright 2017 Thomas W. Doeppner. All rights reserved.
CS 138: Dynamo CS 138 XXIV 1 Copyright 2017 Thomas W. Doeppner. All rights reserved. Dynamo Highly available and scalable distributed data store Manages state of services that have high reliability and
More informationWhy NoSQL? Why Riak?
Why NoSQL? Why Riak? Justin Sheehy justin@basho.com 1 What's all of this NoSQL nonsense? Riak Voldemort HBase MongoDB Neo4j Cassandra CouchDB Membase Redis (and the list goes on...) 2 What went wrong with
More informationCassandra- A Distributed Database
Cassandra- A Distributed Database Tulika Gupta Department of Information Technology Poornima Institute of Engineering and Technology Jaipur, Rajasthan, India Abstract- A relational database is a traditional
More information