SlideShare a Scribd company logo
1 of 55
Using Cassandra in your Web Applications Tom Melendez, Yahoo!
Why do we need another DB? We’re really like MySQL Everyone knows MySQL and if they don’t, they definitely know SQL, Codd, Normalization etc. Lots of tools are based on SQL backends: 3rd party home grown
Should I consider NoSQL? Well, maybe There’s a gazillion NoSQL solutions out there If you’re already using Memcached on top of your db, then you should look closely at NoSQL, as you’ve already identified an issue with your current infrastructure.
Cassandra: Overview Eventually consistent Highly Available Really fast reads, Really fast writes Flexible schemas Distributed No “Master” - No Single Point of Failure BigTable plus Dynamo written in Java
A little context SQL Joins can be expensive Sharding can be a PITA Master is a point of failure (that can be mitigated but we all know its painful) The data really might not be that important RIGHT NOW. Oh yeah, someone got tired of lousy response times
A little history Released by Facebook as Open Source Hosted at Google Code for a bit Now an Apache Project Based on: Amazon’s Dynamo All nodes are Equal (no master) partitioning/replication Google’s Big Table Column Families
Sounds great, right? When do I throw away our SQL DB? When do I get my promotion? When do I go on vacation? Not So Fast.
What you talkin’ about, Willis?
You WILL see this slide again You will need to rewrite code and probably re-arch the application You will need to run in parallel for testing You will need training for your Dev and Ops You will need to develop new tools and processes Cassandra isn’t the only NoSQL option You’ll (likely) still need/want SQL somewhere in your infrastructure
CAP Theorem Consistency – how consistent is the data across nodes? Availability – how available is the system? Partition Tolerance – will the system function if we lose a piece of it? CAP Theorem basically says you get to pick 2 of the above. (Anyone else reminded of: “Good, Fast and Cheap, pick two”?)
CAP and Cassandra The tradeoff between CAP are tunable by the client on a per transaction basis For example, when adding a user record, you could insist that this transaction is CONSISTENCY.ALL if you wanted. To really get the benefit Cassandra, you need to look at what data DOES NOT need CONSISTENCY.ALL
Consistency Levels: Writes
Consistency Levels: Reads
Running Cassandra Does it fit in your infrastructure? Clustering/Partitioning Replication/Snitching Monitoring Tuning Tools/Utilities A couple exist, but you’ll likely need to build your own or at least augment what’s available
Clustering The ring Each node has a unique token (dependent on the Partitioner used) Nodes are responsible for their own tokens plus the node previous to it the token determines on which node rows are stored
Partitioning How data is stored on the cluster Random Order Preserving You can implement your own Custom Partitioning
Partitioning: Types Random Default Good distribution of data across cluster Example usage: logging application Order Preserving Good for range queries OPP has seen some issues on the mailing list lately Custom implement IPartitioner to create your own
Operations: Replication First replica is whatever node claims that range should that node fail But the rest are determined with replication strategies You can tell Cassandra if the nodes are in a rack via IReplicaPlacementStrategy RackUnawareStrategy RackAwareStrategy You can create your own Replication factor – how many copies of the data do we want These options go in conf/storage-conf.xml
Operations: Snitching Telling Cassandra the physical location of nodes EndPoint – figure out based on IP address PropertySnitch – individual IPs to datacenters/racks DatacenterEndpointSnitch – give it subnets and datacenters
Operations - Monitoring IMO, It is critical that you get this working immediately (i.e. as soon as you have something running) Basically requires being able to run JMX queries and ideally store this data over time. Advice: watch the mailing list.  I’m betting a HOWTO will pop up soon as we all have the same problem.
Operations - Tuning You’ve set up monitoring, right? As you add ColumnFamilies, tuning might change Things you tune: Memtables (in mem structure: like a write-back cache) Heap Sizing: don’t ramp up the heap without testing first key cache: probably want to raise this for reads row cache
Utilities: NodeTool Really important.  Helps you manage your cluster.  Find under the bin/ dir in the download get some disk storage stats heap memory usage data snapshot decommission a node move a node
Utilities: cassandra-cli This is NOT the equivalent of: mysql> (although it does provide a prompt) the mysql executable You can do basic get/set operations and some other stuff It is really meant to check and see if things are working Maybe one day it will grow into something more
Utilities: cassandra-cli Example: cassandra> set Keyspace1.Standard1['user']['tom'] = 'cool'    Value inserted. cassandra> count Keyspace1.Standard1['user']               1 columns cassandra> get Keyspace1.Standard1['user']['tom']          => (column=746f6d, value=cool, timestamp=1286875497246000) cassandra> show api version 2.2.0
Other Utilities stress.py – helps you test the performance of your cluster. run periodically against your cluster(s) be prepared with these results when asking for perf help on the mailing list binary-memtable – a bulk loader that avoids some of the Thrift overhead.  Use with caution.
Data Model Simply put, it is similar to a multi-dimensional array The general strategy is denormalized data, sacrificing disk space for speed/efficiency Think about your queries (your DBAs will like this, but won’t like the way it is done!) You’ll end up getting very creative You need to know your queries in advance, they ultimately define your schema.
Data Model Again, keep in mind that you’re (probably) after denormalizing. I know it’s painful.  Terms you’ll see: Keyspaces Column Families SuperColumns Indexes Queries
Data Model Column Family Think of it as a DB table Column Key-Value Pair (NOT just a value, like a DB column) they also have a timestamp SuperColumn Columns inside a column So, you have a key, and its value are columns no timestamp Keyspace – like a namespace, generally 1 per app
Data Model Indexes and Queries Here is where you get creative Regardless of the partitioner, rows are always stored sorted by key Column sorting:  CompareWith  and CompareSubcolumnsWith
Data Model: Indexes and Queries Your bag of tricks include: creating column families for each query getting the row key to be the WHERE of your SQL query using column and SuperColumn names as “values” columns are stored sorted within the row
Data Model: Example Example data set: “b”: {“name”:”Ben”, “street”:”1234 Oak St.”, “city”:”Seattle”, “state”:”WA”}  “jason”: {”name”:”Jason”, “street”:”456 First Ave.”, “city”:”Bellingham”, “state”:”WA”}  “zack”: {”name”: “Zack”, “street”: “4321 Pine St.”, “city”: “Seattle”, “state”: “WA”}  “jen1982”: {”name”:”Jennifer”, “street”:”1120 Foo Lane”, “city”:”San Francisco”, “state”:”CA”}  “albert”: {”name”:”Albert”, “street”:”2364 South St.”, “city”:”Boston”, “state”:”MA”} (Taken from Benjamin Black’s presentation on indexing – twitter: @b6n)
Data Model: Example Given that data set, we want to say: SELECT name FROM Users WHERE state=“WA” We create a ColumnFamily:<ColumnFamily Name=”LocationUserIndexSCF”  CompareWith=”UTF8Type”  CompareSubcolumnsWith=”UTF8Type”  ColumnType=”Super” />  (Taken from Benjamin Black’s presentation on indexing – twitter: @b6n)
Data Model: Example Which looks like this: [state]: {                 [city1]: {[name1]:[user1], [name2]:[user2], ... },                 [city2]: {[name3]:[user3], [name4]:[user4], ... },                ...                [cityX]: {[name5]:[user5], [name6]:[user6], ... }  } State is the row key, so we can select by it and we’ll get the city grouping and name sorting basically for free. (Taken from Benjamin Black’s presentation on indexing – twitter @b6n)
Talking to Cassandra Generally two ways to do this: Native clients (ideal) Thrift Avro support is coming All of the PHP clients are still very Alpha All the PHP clients use Thrift that I’ve seen If you can, please use them and file bugs. Or even better than that – FIX IT YOURSELF! If you need something more stable, use Thrift
PHP Clients Pandra (LGPL)  PHP Cassa – pycassa port  Simple Cassie (New BSD License)  Prophet (PHP License) Clients in other languages are further along Thanks to Chris Barber (@cb1inc) for this list
Raw Cassandra API These are wrapped differently per client but generally exposed by thrift.  These are just the major data manip methods, there are others to gather information, etc.. Full list is here: http://wiki.apache.org/cassandra/API
Raw Cassandra API get get_count get_key_range get_range_slices get_slice multiget_slice insert batch_mutate remove truncate
What is Thrift? Thrift is a remote procedure call framework developed at Facebook for "scalable cross-language services development” – Wikipedia In short, you define a .thrift file (IDL file), with data structures, services, etc. and run the “thrift compiler” and get code, which you then use PHP, Java, Perl, Python, C#, Erlang, Ruby (and probably others) are supported thrift -php myproject.thrift is what you run Generated files are in a dir called: gen-php Then go in and add your logic
Example IDL file Heavily Snipped from: http://wiki.apache.org/thrift/Tutorial # Thrift Tutorial (heavily snipped) # Mark Slee (mcslee@facebook.com) # C and C++ comments also supported include "shared.thrift" namespace phptutorial service Calculator extends shared.SharedService {    void ping(),    i32 add(1:i32 num1, 2:i32 num2),    i32 calculate(1:i32 logid, 2:Work w) throws (1:InvalidOperation ouch), oneway void zip(), }
Installing Thrift and the PHP ext Download and install Thrift http://incubator.apache.org/thrift/download/ To use PHP, you install the PHP extension “thrift_protocol” You’ll find this in the Thrift download above Steps cd PATH-TO-THRIFT/lib/php/src/ext/thrift_protocol phpize && ./configure --enable-thrift_protocol && make sudo cp modules/thrift_protocol.so /php/ext/dir add extension=thrift_protocol.so to the appropriate php.ini file You really need APC, too (http://www.php.net/apc)
PHP Thrift Example http://wiki.apache.org/cassandra/ThriftExamples#PHP
So, who’s using this thing? Big and small companies alike Not sure if they’re applications of Cassandra are mission-critical Yahoo! is NOT a user, but we have our own implementation, and that implementation IS mission critical.  Do a search for “PNUTS”
Facebook – Inbox search
Heavy users, but not for tweets.  Yet.
Probably the biggest consumer-facing users of Cassandra
Digg - continued These guys have provided a lot Patches Documentation/Blogs/Advocacy LazyBoy Python client: http://github.com/digg/lazyboy#readme
Not totally sure, probably logging the massive amounts of data the generate from routers, switches and other hardware http://www.rackspacecloud.com/blog/2010/06/07/speaking-session-on-cassandra-at-velocity-2010/
Others using Cassandra Comcast, Cisco, CBS Interactive http://www.dbthink.com/?p=183
Competitors, sort of CouchDB – document db, accessible via javascript and REST HBase – no SOPF, Column Families, runs on top of Hadoop Memcached – used with MySQL, FB are big users MongoDB – cool online shell; k/v store, document db Redis – see Cassandra vs. Redispresentation by @tlossen from NoSQL Frankfurt 9/28/2010 Voldemort – distributed db, built by LinkedIn
Cassandra and Hadoop and Pig/Hive Yes, it is possible, I haven’t done it myself 0.6x Cassandra - Hadoop M/R jobs can read from Cassandra  0.7x Cassandra – Hadoop M/R jobs can write to it (again, according to the docs) Pig: own implementation of LoadFunc; Hive work has been started See:  http://wiki.apache.org/cassandra/HadoopSupport github.com/stuhood/cassandra-summit-demo slideshare.net/jeromatron cassandrahadoop-4399672 Hive: https://issues.apache.org/jira/browse/CASSANDRA-913
Developing Cassandra itself Using Eclipse http://wiki.apache.org/cassandra/RunningCassandraInEclipse
My personal recommendations Not that you asked. Understand that this is bleeding-edge You’re giving up a lot of SQL comforts Evaluate if you really need this (like anything else) If so, go with the latest and greatest and create a procedure to keep you running the latest and greatest (that would be 0.7x) Contribute back – it is good for your company and for you. Consider commercial support: http://www.riptano.com(I’m not affiliated in any way)
Think about during your evaluation: Are we just in another cycle? Fat client, thin client, Big bandwidth, little bandwidth, big transactions, micro transactions Have we been here before? Remember dbase, Foxpro, Sleepycat/BerkeleyDB? Is it just a technology Fad? How many people developed in WML/HDML only have phones support full HTML/JS? Do we all need native Iphone Apps?
I told you that you’d see this again… You will need to rewrite code and probably re-arch the application You will need to run in parallel for testing You will need training for your Dev and Ops You will need to develop new tools and processes Cassandra isn’t the only NoSQL option You’ll (likely) still need/want SQL
Thanks! http://wiki.apache.org/cassandra/GettingStarted http:///www.riptano.com/blog/slides-and-videos-cassandra-summit-2010

More Related Content

What's hot

How Netflix Tunes EC2 Instances for Performance
How Netflix Tunes EC2 Instances for PerformanceHow Netflix Tunes EC2 Instances for Performance
How Netflix Tunes EC2 Instances for PerformanceBrendan Gregg
 
Parquet Hadoop Summit 2013
Parquet Hadoop Summit 2013Parquet Hadoop Summit 2013
Parquet Hadoop Summit 2013Julien Le Dem
 
Apache Arrow: In Theory, In Practice
Apache Arrow: In Theory, In PracticeApache Arrow: In Theory, In Practice
Apache Arrow: In Theory, In PracticeDremio Corporation
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to RedisDvir Volk
 
Building a Streaming Microservice Architecture: with Apache Spark Structured ...
Building a Streaming Microservice Architecture: with Apache Spark Structured ...Building a Streaming Microservice Architecture: with Apache Spark Structured ...
Building a Streaming Microservice Architecture: with Apache Spark Structured ...Databricks
 
Your first ClickHouse data warehouse
Your first ClickHouse data warehouseYour first ClickHouse data warehouse
Your first ClickHouse data warehouseAltinity Ltd
 
Exploring Java Heap Dumps (Oracle Code One 2018)
Exploring Java Heap Dumps (Oracle Code One 2018)Exploring Java Heap Dumps (Oracle Code One 2018)
Exploring Java Heap Dumps (Oracle Code One 2018)Ryan Cuprak
 
Everything you always wanted to know about Redis but were afraid to ask
Everything you always wanted to know about Redis but were afraid to askEverything you always wanted to know about Redis but were afraid to ask
Everything you always wanted to know about Redis but were afraid to askCarlos Abalde
 
HBase.pptx
HBase.pptxHBase.pptx
HBase.pptxSadhik7
 
HDFS Trunncate: Evolving Beyond Write-Once Semantics
HDFS Trunncate: Evolving Beyond Write-Once SemanticsHDFS Trunncate: Evolving Beyond Write-Once Semantics
HDFS Trunncate: Evolving Beyond Write-Once SemanticsDataWorks Summit
 
Json in Postgres - the Roadmap
 Json in Postgres - the Roadmap Json in Postgres - the Roadmap
Json in Postgres - the RoadmapEDB
 
Hive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveHive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveDataWorks Summit
 
Beyond SQL: Speeding up Spark with DataFrames
Beyond SQL: Speeding up Spark with DataFramesBeyond SQL: Speeding up Spark with DataFrames
Beyond SQL: Speeding up Spark with DataFramesDatabricks
 
Working with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBWorking with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBScaleGrid.io
 
Introducing DataFrames in Spark for Large Scale Data Science
Introducing DataFrames in Spark for Large Scale Data ScienceIntroducing DataFrames in Spark for Large Scale Data Science
Introducing DataFrames in Spark for Large Scale Data ScienceDatabricks
 
Redis overview for Software Architecture Forum
Redis overview for Software Architecture ForumRedis overview for Software Architecture Forum
Redis overview for Software Architecture ForumChristopher Spring
 
Capacity Planning For Your Growing MongoDB Cluster
Capacity Planning For Your Growing MongoDB ClusterCapacity Planning For Your Growing MongoDB Cluster
Capacity Planning For Your Growing MongoDB ClusterMongoDB
 

What's hot (20)

File Format Benchmark - Avro, JSON, ORC & Parquet
File Format Benchmark - Avro, JSON, ORC & ParquetFile Format Benchmark - Avro, JSON, ORC & Parquet
File Format Benchmark - Avro, JSON, ORC & Parquet
 
Beautiful soup
Beautiful soupBeautiful soup
Beautiful soup
 
How Netflix Tunes EC2 Instances for Performance
How Netflix Tunes EC2 Instances for PerformanceHow Netflix Tunes EC2 Instances for Performance
How Netflix Tunes EC2 Instances for Performance
 
Parquet Hadoop Summit 2013
Parquet Hadoop Summit 2013Parquet Hadoop Summit 2013
Parquet Hadoop Summit 2013
 
Apache Arrow: In Theory, In Practice
Apache Arrow: In Theory, In PracticeApache Arrow: In Theory, In Practice
Apache Arrow: In Theory, In Practice
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to Redis
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to Redis
 
Building a Streaming Microservice Architecture: with Apache Spark Structured ...
Building a Streaming Microservice Architecture: with Apache Spark Structured ...Building a Streaming Microservice Architecture: with Apache Spark Structured ...
Building a Streaming Microservice Architecture: with Apache Spark Structured ...
 
Your first ClickHouse data warehouse
Your first ClickHouse data warehouseYour first ClickHouse data warehouse
Your first ClickHouse data warehouse
 
Exploring Java Heap Dumps (Oracle Code One 2018)
Exploring Java Heap Dumps (Oracle Code One 2018)Exploring Java Heap Dumps (Oracle Code One 2018)
Exploring Java Heap Dumps (Oracle Code One 2018)
 
Everything you always wanted to know about Redis but were afraid to ask
Everything you always wanted to know about Redis but were afraid to askEverything you always wanted to know about Redis but were afraid to ask
Everything you always wanted to know about Redis but were afraid to ask
 
HBase.pptx
HBase.pptxHBase.pptx
HBase.pptx
 
HDFS Trunncate: Evolving Beyond Write-Once Semantics
HDFS Trunncate: Evolving Beyond Write-Once SemanticsHDFS Trunncate: Evolving Beyond Write-Once Semantics
HDFS Trunncate: Evolving Beyond Write-Once Semantics
 
Json in Postgres - the Roadmap
 Json in Postgres - the Roadmap Json in Postgres - the Roadmap
Json in Postgres - the Roadmap
 
Hive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep DiveHive + Tez: A Performance Deep Dive
Hive + Tez: A Performance Deep Dive
 
Beyond SQL: Speeding up Spark with DataFrames
Beyond SQL: Speeding up Spark with DataFramesBeyond SQL: Speeding up Spark with DataFrames
Beyond SQL: Speeding up Spark with DataFrames
 
Working with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBWorking with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDB
 
Introducing DataFrames in Spark for Large Scale Data Science
Introducing DataFrames in Spark for Large Scale Data ScienceIntroducing DataFrames in Spark for Large Scale Data Science
Introducing DataFrames in Spark for Large Scale Data Science
 
Redis overview for Software Architecture Forum
Redis overview for Software Architecture ForumRedis overview for Software Architecture Forum
Redis overview for Software Architecture Forum
 
Capacity Planning For Your Growing MongoDB Cluster
Capacity Planning For Your Growing MongoDB ClusterCapacity Planning For Your Growing MongoDB Cluster
Capacity Planning For Your Growing MongoDB Cluster
 

Viewers also liked

NodeJS : Communication and Round Robin Way
NodeJS : Communication and Round Robin WayNodeJS : Communication and Round Robin Way
NodeJS : Communication and Round Robin WayEdureka!
 
Node.js and Cassandra
Node.js and CassandraNode.js and Cassandra
Node.js and CassandraStratio
 
Application Development with Apache Cassandra as a Service
Application Development with Apache Cassandra as a ServiceApplication Development with Apache Cassandra as a Service
Application Development with Apache Cassandra as a ServiceWSO2
 
Cassandra at NoSql Matters 2012
Cassandra at NoSql Matters 2012Cassandra at NoSql Matters 2012
Cassandra at NoSql Matters 2012jbellis
 
Cassandra DataTables Using RESTful API
Cassandra DataTables Using RESTful APICassandra DataTables Using RESTful API
Cassandra DataTables Using RESTful APISimran Kedia
 
Cassandra NodeJS driver & NodeJS Paris
Cassandra NodeJS driver & NodeJS ParisCassandra NodeJS driver & NodeJS Paris
Cassandra NodeJS driver & NodeJS ParisDuyhai Doan
 
Cassandra Java APIs Old and New – A Comparison
Cassandra Java APIs Old and New – A ComparisonCassandra Java APIs Old and New – A Comparison
Cassandra Java APIs Old and New – A Comparisonshsedghi
 
Developing with Cassandra
Developing with CassandraDeveloping with Cassandra
Developing with CassandraSperasoft
 

Viewers also liked (8)

NodeJS : Communication and Round Robin Way
NodeJS : Communication and Round Robin WayNodeJS : Communication and Round Robin Way
NodeJS : Communication and Round Robin Way
 
Node.js and Cassandra
Node.js and CassandraNode.js and Cassandra
Node.js and Cassandra
 
Application Development with Apache Cassandra as a Service
Application Development with Apache Cassandra as a ServiceApplication Development with Apache Cassandra as a Service
Application Development with Apache Cassandra as a Service
 
Cassandra at NoSql Matters 2012
Cassandra at NoSql Matters 2012Cassandra at NoSql Matters 2012
Cassandra at NoSql Matters 2012
 
Cassandra DataTables Using RESTful API
Cassandra DataTables Using RESTful APICassandra DataTables Using RESTful API
Cassandra DataTables Using RESTful API
 
Cassandra NodeJS driver & NodeJS Paris
Cassandra NodeJS driver & NodeJS ParisCassandra NodeJS driver & NodeJS Paris
Cassandra NodeJS driver & NodeJS Paris
 
Cassandra Java APIs Old and New – A Comparison
Cassandra Java APIs Old and New – A ComparisonCassandra Java APIs Old and New – A Comparison
Cassandra Java APIs Old and New – A Comparison
 
Developing with Cassandra
Developing with CassandraDeveloping with Cassandra
Developing with Cassandra
 

Similar to Using Cassandra in Web Apps

Nyc summit intro_to_cassandra
Nyc summit intro_to_cassandraNyc summit intro_to_cassandra
Nyc summit intro_to_cassandrazznate
 
Front Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesFront Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesJon Meredith
 
SQL or NoSQL, that is the question!
SQL or NoSQL, that is the question!SQL or NoSQL, that is the question!
SQL or NoSQL, that is the question!Andraz Tori
 
Storage cassandra
Storage   cassandraStorage   cassandra
Storage cassandraPL dream
 
Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...
Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...
Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...javier ramirez
 
Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)zznate
 
Bhupeshbansal bigdata
Bhupeshbansal bigdata Bhupeshbansal bigdata
Bhupeshbansal bigdata Bhupesh Bansal
 
Schemaless Databases
Schemaless DatabasesSchemaless Databases
Schemaless DatabasesDan Gunter
 
Scaling opensimulator inventory using nosql
Scaling opensimulator inventory using nosqlScaling opensimulator inventory using nosql
Scaling opensimulator inventory using nosqlDavid Daeschler
 
Breakthrough OLAP performance with Cassandra and Spark
Breakthrough OLAP performance with Cassandra and SparkBreakthrough OLAP performance with Cassandra and Spark
Breakthrough OLAP performance with Cassandra and SparkEvan Chan
 
Architecture by Accident
Architecture by AccidentArchitecture by Accident
Architecture by AccidentGleicon Moraes
 
Big data vahidamiri-tabriz-13960226-datastack.ir
Big data vahidamiri-tabriz-13960226-datastack.irBig data vahidamiri-tabriz-13960226-datastack.ir
Big data vahidamiri-tabriz-13960226-datastack.irdatastack
 
http://www.hfadeel.com/Blog/?p=151
http://www.hfadeel.com/Blog/?p=151http://www.hfadeel.com/Blog/?p=151
http://www.hfadeel.com/Blog/?p=151xlight
 
UnConference for Georgia Southern Computer Science March 31, 2015
UnConference for Georgia Southern Computer Science March 31, 2015UnConference for Georgia Southern Computer Science March 31, 2015
UnConference for Georgia Southern Computer Science March 31, 2015Christopher Curtin
 
Architectural anti-patterns for data handling
Architectural anti-patterns for data handlingArchitectural anti-patterns for data handling
Architectural anti-patterns for data handlingGleicon Moraes
 
DrupalCampLA 2011: Drupal backend-performance
DrupalCampLA 2011: Drupal backend-performanceDrupalCampLA 2011: Drupal backend-performance
DrupalCampLA 2011: Drupal backend-performanceAshok Modi
 

Similar to Using Cassandra in Web Apps (20)

No sql
No sqlNo sql
No sql
 
Nyc summit intro_to_cassandra
Nyc summit intro_to_cassandraNyc summit intro_to_cassandra
Nyc summit intro_to_cassandra
 
NoSql Database
NoSql DatabaseNoSql Database
NoSql Database
 
Front Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesFront Range PHP NoSQL Databases
Front Range PHP NoSQL Databases
 
SQL or NoSQL, that is the question!
SQL or NoSQL, that is the question!SQL or NoSQL, that is the question!
SQL or NoSQL, that is the question!
 
Storage cassandra
Storage   cassandraStorage   cassandra
Storage cassandra
 
Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...
Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...
Ingesting Over Four Million Rows Per Second With QuestDB Timeseries Database ...
 
Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)Introduciton to Apache Cassandra for Java Developers (JavaOne)
Introduciton to Apache Cassandra for Java Developers (JavaOne)
 
Bhupeshbansal bigdata
Bhupeshbansal bigdata Bhupeshbansal bigdata
Bhupeshbansal bigdata
 
Schemaless Databases
Schemaless DatabasesSchemaless Databases
Schemaless Databases
 
Scaling opensimulator inventory using nosql
Scaling opensimulator inventory using nosqlScaling opensimulator inventory using nosql
Scaling opensimulator inventory using nosql
 
Breakthrough OLAP performance with Cassandra and Spark
Breakthrough OLAP performance with Cassandra and SparkBreakthrough OLAP performance with Cassandra and Spark
Breakthrough OLAP performance with Cassandra and Spark
 
Architecture by Accident
Architecture by AccidentArchitecture by Accident
Architecture by Accident
 
Big data vahidamiri-tabriz-13960226-datastack.ir
Big data vahidamiri-tabriz-13960226-datastack.irBig data vahidamiri-tabriz-13960226-datastack.ir
Big data vahidamiri-tabriz-13960226-datastack.ir
 
http://www.hfadeel.com/Blog/?p=151
http://www.hfadeel.com/Blog/?p=151http://www.hfadeel.com/Blog/?p=151
http://www.hfadeel.com/Blog/?p=151
 
UnConference for Georgia Southern Computer Science March 31, 2015
UnConference for Georgia Southern Computer Science March 31, 2015UnConference for Georgia Southern Computer Science March 31, 2015
UnConference for Georgia Southern Computer Science March 31, 2015
 
Architectural anti-patterns for data handling
Architectural anti-patterns for data handlingArchitectural anti-patterns for data handling
Architectural anti-patterns for data handling
 
No sql
No sqlNo sql
No sql
 
Nosql seminar
Nosql seminarNosql seminar
Nosql seminar
 
DrupalCampLA 2011: Drupal backend-performance
DrupalCampLA 2011: Drupal backend-performanceDrupalCampLA 2011: Drupal backend-performance
DrupalCampLA 2011: Drupal backend-performance
 

Recently uploaded

APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDGMarianaLemus7
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 

Recently uploaded (20)

APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDG
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 

Using Cassandra in Web Apps

  • 1. Using Cassandra in your Web Applications Tom Melendez, Yahoo!
  • 2. Why do we need another DB? We’re really like MySQL Everyone knows MySQL and if they don’t, they definitely know SQL, Codd, Normalization etc. Lots of tools are based on SQL backends: 3rd party home grown
  • 3. Should I consider NoSQL? Well, maybe There’s a gazillion NoSQL solutions out there If you’re already using Memcached on top of your db, then you should look closely at NoSQL, as you’ve already identified an issue with your current infrastructure.
  • 4. Cassandra: Overview Eventually consistent Highly Available Really fast reads, Really fast writes Flexible schemas Distributed No “Master” - No Single Point of Failure BigTable plus Dynamo written in Java
  • 5. A little context SQL Joins can be expensive Sharding can be a PITA Master is a point of failure (that can be mitigated but we all know its painful) The data really might not be that important RIGHT NOW. Oh yeah, someone got tired of lousy response times
  • 6. A little history Released by Facebook as Open Source Hosted at Google Code for a bit Now an Apache Project Based on: Amazon’s Dynamo All nodes are Equal (no master) partitioning/replication Google’s Big Table Column Families
  • 7. Sounds great, right? When do I throw away our SQL DB? When do I get my promotion? When do I go on vacation? Not So Fast.
  • 8. What you talkin’ about, Willis?
  • 9. You WILL see this slide again You will need to rewrite code and probably re-arch the application You will need to run in parallel for testing You will need training for your Dev and Ops You will need to develop new tools and processes Cassandra isn’t the only NoSQL option You’ll (likely) still need/want SQL somewhere in your infrastructure
  • 10. CAP Theorem Consistency – how consistent is the data across nodes? Availability – how available is the system? Partition Tolerance – will the system function if we lose a piece of it? CAP Theorem basically says you get to pick 2 of the above. (Anyone else reminded of: “Good, Fast and Cheap, pick two”?)
  • 11. CAP and Cassandra The tradeoff between CAP are tunable by the client on a per transaction basis For example, when adding a user record, you could insist that this transaction is CONSISTENCY.ALL if you wanted. To really get the benefit Cassandra, you need to look at what data DOES NOT need CONSISTENCY.ALL
  • 14. Running Cassandra Does it fit in your infrastructure? Clustering/Partitioning Replication/Snitching Monitoring Tuning Tools/Utilities A couple exist, but you’ll likely need to build your own or at least augment what’s available
  • 15. Clustering The ring Each node has a unique token (dependent on the Partitioner used) Nodes are responsible for their own tokens plus the node previous to it the token determines on which node rows are stored
  • 16. Partitioning How data is stored on the cluster Random Order Preserving You can implement your own Custom Partitioning
  • 17. Partitioning: Types Random Default Good distribution of data across cluster Example usage: logging application Order Preserving Good for range queries OPP has seen some issues on the mailing list lately Custom implement IPartitioner to create your own
  • 18. Operations: Replication First replica is whatever node claims that range should that node fail But the rest are determined with replication strategies You can tell Cassandra if the nodes are in a rack via IReplicaPlacementStrategy RackUnawareStrategy RackAwareStrategy You can create your own Replication factor – how many copies of the data do we want These options go in conf/storage-conf.xml
  • 19. Operations: Snitching Telling Cassandra the physical location of nodes EndPoint – figure out based on IP address PropertySnitch – individual IPs to datacenters/racks DatacenterEndpointSnitch – give it subnets and datacenters
  • 20. Operations - Monitoring IMO, It is critical that you get this working immediately (i.e. as soon as you have something running) Basically requires being able to run JMX queries and ideally store this data over time. Advice: watch the mailing list. I’m betting a HOWTO will pop up soon as we all have the same problem.
  • 21. Operations - Tuning You’ve set up monitoring, right? As you add ColumnFamilies, tuning might change Things you tune: Memtables (in mem structure: like a write-back cache) Heap Sizing: don’t ramp up the heap without testing first key cache: probably want to raise this for reads row cache
  • 22. Utilities: NodeTool Really important. Helps you manage your cluster. Find under the bin/ dir in the download get some disk storage stats heap memory usage data snapshot decommission a node move a node
  • 23. Utilities: cassandra-cli This is NOT the equivalent of: mysql> (although it does provide a prompt) the mysql executable You can do basic get/set operations and some other stuff It is really meant to check and see if things are working Maybe one day it will grow into something more
  • 24. Utilities: cassandra-cli Example: cassandra> set Keyspace1.Standard1['user']['tom'] = 'cool' Value inserted. cassandra> count Keyspace1.Standard1['user'] 1 columns cassandra> get Keyspace1.Standard1['user']['tom'] => (column=746f6d, value=cool, timestamp=1286875497246000) cassandra> show api version 2.2.0
  • 25. Other Utilities stress.py – helps you test the performance of your cluster. run periodically against your cluster(s) be prepared with these results when asking for perf help on the mailing list binary-memtable – a bulk loader that avoids some of the Thrift overhead. Use with caution.
  • 26. Data Model Simply put, it is similar to a multi-dimensional array The general strategy is denormalized data, sacrificing disk space for speed/efficiency Think about your queries (your DBAs will like this, but won’t like the way it is done!) You’ll end up getting very creative You need to know your queries in advance, they ultimately define your schema.
  • 27. Data Model Again, keep in mind that you’re (probably) after denormalizing. I know it’s painful.  Terms you’ll see: Keyspaces Column Families SuperColumns Indexes Queries
  • 28. Data Model Column Family Think of it as a DB table Column Key-Value Pair (NOT just a value, like a DB column) they also have a timestamp SuperColumn Columns inside a column So, you have a key, and its value are columns no timestamp Keyspace – like a namespace, generally 1 per app
  • 29. Data Model Indexes and Queries Here is where you get creative Regardless of the partitioner, rows are always stored sorted by key Column sorting: CompareWith and CompareSubcolumnsWith
  • 30. Data Model: Indexes and Queries Your bag of tricks include: creating column families for each query getting the row key to be the WHERE of your SQL query using column and SuperColumn names as “values” columns are stored sorted within the row
  • 31. Data Model: Example Example data set: “b”: {“name”:”Ben”, “street”:”1234 Oak St.”, “city”:”Seattle”, “state”:”WA”} “jason”: {”name”:”Jason”, “street”:”456 First Ave.”, “city”:”Bellingham”, “state”:”WA”} “zack”: {”name”: “Zack”, “street”: “4321 Pine St.”, “city”: “Seattle”, “state”: “WA”} “jen1982”: {”name”:”Jennifer”, “street”:”1120 Foo Lane”, “city”:”San Francisco”, “state”:”CA”} “albert”: {”name”:”Albert”, “street”:”2364 South St.”, “city”:”Boston”, “state”:”MA”} (Taken from Benjamin Black’s presentation on indexing – twitter: @b6n)
  • 32. Data Model: Example Given that data set, we want to say: SELECT name FROM Users WHERE state=“WA” We create a ColumnFamily:<ColumnFamily Name=”LocationUserIndexSCF” CompareWith=”UTF8Type” CompareSubcolumnsWith=”UTF8Type” ColumnType=”Super” /> (Taken from Benjamin Black’s presentation on indexing – twitter: @b6n)
  • 33. Data Model: Example Which looks like this: [state]: { [city1]: {[name1]:[user1], [name2]:[user2], ... }, [city2]: {[name3]:[user3], [name4]:[user4], ... }, ... [cityX]: {[name5]:[user5], [name6]:[user6], ... } } State is the row key, so we can select by it and we’ll get the city grouping and name sorting basically for free. (Taken from Benjamin Black’s presentation on indexing – twitter @b6n)
  • 34. Talking to Cassandra Generally two ways to do this: Native clients (ideal) Thrift Avro support is coming All of the PHP clients are still very Alpha All the PHP clients use Thrift that I’ve seen If you can, please use them and file bugs. Or even better than that – FIX IT YOURSELF! If you need something more stable, use Thrift
  • 35. PHP Clients Pandra (LGPL) PHP Cassa – pycassa port Simple Cassie (New BSD License) Prophet (PHP License) Clients in other languages are further along Thanks to Chris Barber (@cb1inc) for this list
  • 36. Raw Cassandra API These are wrapped differently per client but generally exposed by thrift. These are just the major data manip methods, there are others to gather information, etc.. Full list is here: http://wiki.apache.org/cassandra/API
  • 37. Raw Cassandra API get get_count get_key_range get_range_slices get_slice multiget_slice insert batch_mutate remove truncate
  • 38. What is Thrift? Thrift is a remote procedure call framework developed at Facebook for "scalable cross-language services development” – Wikipedia In short, you define a .thrift file (IDL file), with data structures, services, etc. and run the “thrift compiler” and get code, which you then use PHP, Java, Perl, Python, C#, Erlang, Ruby (and probably others) are supported thrift -php myproject.thrift is what you run Generated files are in a dir called: gen-php Then go in and add your logic
  • 39. Example IDL file Heavily Snipped from: http://wiki.apache.org/thrift/Tutorial # Thrift Tutorial (heavily snipped) # Mark Slee (mcslee@facebook.com) # C and C++ comments also supported include "shared.thrift" namespace phptutorial service Calculator extends shared.SharedService { void ping(), i32 add(1:i32 num1, 2:i32 num2), i32 calculate(1:i32 logid, 2:Work w) throws (1:InvalidOperation ouch), oneway void zip(), }
  • 40. Installing Thrift and the PHP ext Download and install Thrift http://incubator.apache.org/thrift/download/ To use PHP, you install the PHP extension “thrift_protocol” You’ll find this in the Thrift download above Steps cd PATH-TO-THRIFT/lib/php/src/ext/thrift_protocol phpize && ./configure --enable-thrift_protocol && make sudo cp modules/thrift_protocol.so /php/ext/dir add extension=thrift_protocol.so to the appropriate php.ini file You really need APC, too (http://www.php.net/apc)
  • 41. PHP Thrift Example http://wiki.apache.org/cassandra/ThriftExamples#PHP
  • 42. So, who’s using this thing? Big and small companies alike Not sure if they’re applications of Cassandra are mission-critical Yahoo! is NOT a user, but we have our own implementation, and that implementation IS mission critical. Do a search for “PNUTS”
  • 44. Heavy users, but not for tweets. Yet.
  • 45. Probably the biggest consumer-facing users of Cassandra
  • 46. Digg - continued These guys have provided a lot Patches Documentation/Blogs/Advocacy LazyBoy Python client: http://github.com/digg/lazyboy#readme
  • 47. Not totally sure, probably logging the massive amounts of data the generate from routers, switches and other hardware http://www.rackspacecloud.com/blog/2010/06/07/speaking-session-on-cassandra-at-velocity-2010/
  • 48. Others using Cassandra Comcast, Cisco, CBS Interactive http://www.dbthink.com/?p=183
  • 49. Competitors, sort of CouchDB – document db, accessible via javascript and REST HBase – no SOPF, Column Families, runs on top of Hadoop Memcached – used with MySQL, FB are big users MongoDB – cool online shell; k/v store, document db Redis – see Cassandra vs. Redispresentation by @tlossen from NoSQL Frankfurt 9/28/2010 Voldemort – distributed db, built by LinkedIn
  • 50. Cassandra and Hadoop and Pig/Hive Yes, it is possible, I haven’t done it myself 0.6x Cassandra - Hadoop M/R jobs can read from Cassandra 0.7x Cassandra – Hadoop M/R jobs can write to it (again, according to the docs) Pig: own implementation of LoadFunc; Hive work has been started See: http://wiki.apache.org/cassandra/HadoopSupport github.com/stuhood/cassandra-summit-demo slideshare.net/jeromatron cassandrahadoop-4399672 Hive: https://issues.apache.org/jira/browse/CASSANDRA-913
  • 51. Developing Cassandra itself Using Eclipse http://wiki.apache.org/cassandra/RunningCassandraInEclipse
  • 52. My personal recommendations Not that you asked. Understand that this is bleeding-edge You’re giving up a lot of SQL comforts Evaluate if you really need this (like anything else) If so, go with the latest and greatest and create a procedure to keep you running the latest and greatest (that would be 0.7x) Contribute back – it is good for your company and for you. Consider commercial support: http://www.riptano.com(I’m not affiliated in any way)
  • 53. Think about during your evaluation: Are we just in another cycle? Fat client, thin client, Big bandwidth, little bandwidth, big transactions, micro transactions Have we been here before? Remember dbase, Foxpro, Sleepycat/BerkeleyDB? Is it just a technology Fad? How many people developed in WML/HDML only have phones support full HTML/JS? Do we all need native Iphone Apps?
  • 54. I told you that you’d see this again… You will need to rewrite code and probably re-arch the application You will need to run in parallel for testing You will need training for your Dev and Ops You will need to develop new tools and processes Cassandra isn’t the only NoSQL option You’ll (likely) still need/want SQL

Editor's Notes

  1. http://blog.medallia.com/2010/05/choosing_a_keyvalue_storage_sy.html
  2. http://www.julianbrowne.com/article/viewer/brewers-cap-theoremhttp://dbmsmusings.blogspot.com/2010/04/problems-with-cap-and-yahoos-little.html
  3. http://www.riptano.com/docs/0.6.5/consistency/levels
  4. http://www.riptano.com/docs/0.6.5/consistency/levels
  5. http://www.riptano.com/docs/0.6.5/operations/clustering
  6. http://www.riptano.com/docs/0.6.5/operations/clusteringhttp://www.slideshare.net/benjaminblack/introduction-to-cassandra-replication-and-consistency
  7. http://www.slideshare.net/benjaminblack/introduction-to-cassandra-replication-and-consistency
  8. You need to know and understand where you started from and where you are now. If you don’t do this, you’ll be on the mailing list having to explain in detail your setup and reporting back the numbers provided by JMX. So, save yourself the trouble and understand how it works from day one.Maybe Cassandra is a good store for holding Cassandra JMX data. 
  9. See: http://www.riptano.com/docs/0.6.5/operations/tuninghttp://wiki.apache.org/cassandra/MemtableSSTablecommit log -&gt; memtablesstableshttp://wiki.apache.org/cassandra/ArchitectureSSTable
  10. nodetool --hlocalhostcfstatsnodetool --hlocalhost ringnodetool --hlocalhost info
  11. http://www.riptano.com/docs/0.6.5/utils/binary-memtable
  12. http://www.slideshare.net/benjaminblack/cassandra-basics-indexing
  13. http://www.slideshare.net/benjaminblack/cassandra-basics-indexing
  14. http://www.slideshare.net/benjaminblack/cassandra-basics-indexing
  15. http://www.riptano.com/docs/0.6.5/api/clientshttp://avro.apache.org/docs/current/
  16. http://wiki.apache.org/cassandra/API
  17. http://chanian.com/2010/05/13/thrift-tutorial-a-php-client/http://incubator.apache.org/thrift/about/http://wiki.apache.org/thrift/ThriftIDL
  18. http://incubator.apache.org/thrift/download/https://wiki.fourkitchens.com/display/PF/Using+Cassandra+with+PHPhttp://www.php.net/apc
  19. http://www.facebook.com/note.php?note_id=24413138919
  20. As of July, Twitter is using Cassandra, but not to store tweets.http://engineering.twitter.com/2010/07/cassandra-at-twitter-today.html
  21. http://project-voldemort.com/http://project-voldemort.com/performance.phphttp://blog.oskarsson.nu/2009/06/nosql-debrief.htmlhttp://static.last.fm/johan/nosql-20090611/vpork_nosql.pdf
  22. http://highscalability.com/blog/2009/10/13/why-are-facebook-digg-and-twitter-so-hard-to-scale.htmlhttp://maxgrinev.com/2010/07/12/do-you-really-need-sql-to-do-it-all-in-cassandra/http://arin.me/blog/wtf-is-a-supercolumn-cassandra-data-modelhttp://www.rackspacecloud.com/blog/2010/02/25/should-you-switch-to-nosql-too/http://www.slideshare.net/jbellis/what-every-developer-should-know-about-database-scalability-pycon-2010http://david415.wordpress.com/2010/09/03/cassandra-data-storage-performance-tool/