Cassandra Lan party

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Meetup Cassandra Lyon: Lan party

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  • Elastic scalability - Allows you to easily add capacity online to accommodate more customers and more data whenever you need.
    Always on architecture - Contains no single point of failure (as with traditional master/slave RDBMS’s and other NoSQL solutions) resulting in continuous availability for business-critical applications that can’t afford to go down, ever.
    Fast linear-scale performance - Enables sub-second response times with linear scalability (double your throughput with two nodes, quadruple it with four, and so on) to deliver response time speeds your customers have come to expect.
    Flexible data storage - Easily accommodates the full range of data formats including: structured, semi-structured and unstructured, that run through today’s modern applications. Also dynamically accommodates changes to your data structures as your data needs evolve.
    Easy data distribution - Gives you maximum flexibility to distribute data where you need by replicating data across multiple datacenters, the cloud and even mixed cloud/on-premise environments – all of which are becoming extremely common deployment environments. Read and write to any node with all changes being automatically synchronized across a cluster.
    Operational simplicity - with all nodes in a cluster being the same, there is no complex configuration to manage so administration duties are greatly simplified.
    Transaction support - Delivers atomicity, isolation and durability of ACID compliance through its use of a commit log to capture all writes and built-in redundancies that ensure data durability in the event of hardware failures, as well as transaction isolation, atomicity, with consistency being tunable.
  • Cassandra Lan party

    1. 1. Meetup Cassandra Lan Party
    2. 2. Sommaire ● Rappels ● Installation réseau et logiciels ● Configuration du cluster ● Tests
    3. 3. Who’s who ● Gérald Quintana o @gerald_quintana o o Formateur Cassandra
    4. 4. Rappels
    5. 5. Key Features Elastic scalability Always on architecture Fast linear-scale performance Flexible data storage Easy data distribution Operational simplicity Transaction support
    6. 6. Cluster ● Noeuds o 1 seul type o 1 IP ● Configuration o cassandra.yaml o o ● Données o CommitLog o Data o Saved caches o Log
    7. 7. Column oriented data model Keyspace Table (ColumnFamily) Row: Row key Column: Clustering key Value TTL Map<PartKey, SortedMap<ClustKey, Column>> Username Timestamp Message Status gquintana 2015-01-15 Meetup Speaking jdoe 2015-01-15 Meetup jdoe 2015-01-16 Holidays Partition Row Key Primary Key
    8. 8. Partition & Consistent hashing ● Hash(Row Key) → Token ● Noeud → Plage de tokens
    9. 9. Replication
    10. 10. Virtual nodes
    11. 11. Multi datacenters ● Physiques o Distribution géographique o Failover ● Logiques o Live backup o Analytique (OLAP) ● Sans ETL ● Replication factor
    12. 12. Réplication: Combien? ● Niveau keyspace create keyspace meetup with replication={ 'class':'NetworkTopologyStrategy', 'lyon':2,'paris':2};
    13. 13. Réplication: Où? ● Niveau node: o SimpleSnitch o RackInferringSnitch  + IP 10.dc.rc.n o PropertyFileSnitch  + o GossipingPropertyFileSnitch  + o EC2Snitch, GoogleCloudSnitch, CloudstackSnitch
    14. 14. Notre cluster Lyon 10.1.rc.n Paris 10.2.rc.n OpsCenter
    15. 15. Au boulot!
    16. 16. Etape 1 Copier/Télécharger ● Java 7 ● Python 2.6+ o 279/ (ou bien paquets apt-get, yum) ● Cassandra 2.0 DSC (DataStax Community) o o cassandra-2.0.11-bin.tar.gz ● DataStax OpsCenter Agent o agent-5.0.2.tar.gz ● Injecteur
    17. 17. Etape 2 Configurer le réseau ● Désactiver le Wifi & le firewall ● Configurer l’IP de manière statique o IP 10.dc.rc.n o Masque ● Pinguer & se faire pinguer
    18. 18. Etape 3 Installer ● Java: JAVA_HOME, java -version ● Python: python --version ● Cassandra o Si besoin, supprimer les data ● OpsCenter Agent ● Synchroniser les horloges Ne pas démarrer Cassandra
    19. 19. Etape 4a Configurer Cassandra ● cassandra.yaml o cluster_name: 'meetup' o listen_address: 10.dc.rc.n o rpc_address: o seed_provider.parameters.seeds:,, o endpoint_snitch: GossipingPropertyFileSnitch o commitlog_directory, data_file_directories, saved_caches_directory Ne pas démarrer Cassandra
    20. 20. Etape 4b Configurer Cassandra ● o dc=lyon|paris, rack=RAC1 ● o ...File=log/system.log ● Vérifier la configuration du voisin Ne pas démarrer Cassandra
    21. 21. Etape 5 Configurer DataStax Agent ● datastax-agent.bat o set JAR=datastax-agent-5.0.2-standalone.jar ● address.yaml o stomp_interface: '' o local_interface: '10.dc.rc.n'
    22. 22. Etape 6 Démarrer Cassandra ● Attendre le Go ● Démarrer Cassandra puis l’Agent ● Surveiller les logs ● Surveiller l’état o du noeud nodetool info o du cluster nodetool status o des tokens nodetool ring ● Surveiller OpsCenter
    23. 23. Etape 7 Initialiser le schéma create keyspace meetup with replication={ 'class':'NetworkTopologyStrategy', 'lyon':2,'paris':2}; create table metric ( host varchar, name varchar, date timestamp, value bigint, primary key ((host,name),date) );
    24. 24. Etape 7 Insérer des données ● Avec cqlsh ● Démarrer l’injecteur describe keyspaces; describe keyspace meetup; use meetup; describe tables; describe table metric; select * from metric; insert into metric(host,name,date,value) values ('localhost','cpu',dateOf(now()), 12);
    25. 25. Scénario 1 Perte d’un noeud ● Hinted handoff ● Surveiller o notetool status o OpsCenter o cqlsh  select * from system.hints
    26. 26. Scénario 2 Ajout d’un noeud ● Streaming ● Surveiller o Cluster: nodetool status o Streaming: nodetool netstats o OpsCenter
    27. 27. Scénario 3 Perte d’un datacenter ● Surveiller o notetool status o OpsCenter
    28. 28. Conclusion ● Les vertues de Cassandra o Tolérance aux pannes o Scalabilité linéaire o Configuration Simple ● Reset configuration réseau o Configuration IP o Réactiver firewall