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3. 12. 2020
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cassandra architecture internals

Node− It is the place where data is stored. And a relational database like PostgreSQL keeps an index (or other data structure, such as a B-tree) for each table index, in order for values in that index to be found efficiently. Automatic sharding is done by NoSQL database like Cassandra whereas almost all older SQL type databases (MySQL, Oracle, Postgres) one need to do sharding manually. You may want to steer clear of this; the Database’s using the master-slave (with or without automatic failover) -MySQL, Postgres, MongoDB, Oracle RAC(note MySQL recent Cluster seems to use master less concept (similar/based on Paxos) but with limitations, read MySQL Galera Cluster), You may want to choose a database that support’s Master-less High Availability( also read Replication ), Cassandra has a peer-to-peer (or “masterless”) distributed “ring” architecture that is elegant, easy to set up, and maintain.In Cassandra, all nodes are the same; there is no concept of a master node, with all nodes communicating with each other via a gossip protocol. Powered by a free Atlassian Confluence Open Source Project License granted to Apache Software Foundation. It introduces all the important concepts needed to understand Cassandra, including enough coverage of internal architecture so you can make optimal decisions. Compaction is the process of reading several SSTables and outputting one SSTable containing the merged, most recent, information. The short answer is “no” technically, but “yes” in effect and its users can and do assume CA. For example, at replication factor 3 a read at consistency level QUORUM would require one digest read in additional to the data read sent to the closest node. https://c.statcounter.com/9397521/0/fe557aad/1/|stats. This approach significantly reduces developer and operational complexity compared to running multiple databases. CREATE TABLE videos (…PRIMARY KEY (videoid)); Example 2: PARTITION KEY == userid, rest of PRIMARY keys are Clustering keys for ordering/sortig the columns. The way to minimize partition reads is to model your data to fit your queries. Understanding the architecture. Understand and tune consistency 2.4. Storage engine Stages are set up in StageManager; currently there are read, write, and stream stages. It's a good example of how to implement a Cassandra client and CLI internals help us to develop custom Cassandra clients or … …. The flush from Memtable to SStable is one operation and the SSTable file once written is immutable (not more updates). LeveledCompactionStrategy provides stricter guarantees at the price of more compaction i/o; see. Commit LogEvery write operation is written to Commit Log. https://aws.amazon.com/blogs/database/amazon-aurora-as-an-alternative-to-oracle-rac/. If some of the nodes are responded with an out-of-date value, Cassandra will return the most recent value to the client. The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. If there is a cache hit, the coordinator can be responded to immediately. The fact that a data read is only submitted to the closest replica is intended as an optimization to avoid sending excessive amounts of data over the network. See the following image to understand the schematic view of how Cassandra uses data replication among the nod… 2. Cassandra Community Webinar: Apache Cassandra Internals. SSTable flush happens periodically when memory is full. To locate the data row's position in SSTables, the following sequence is performed: The key cache is checked for that key/sstable combination. Secondary index queries are covered by RangeSliceCommand. Topics about the Cassandra database. This will mean that the slave (multi oracle instances in different nodes) can scale read, but when it comes to writing things are not that easy. Cluster wide operations track node membership, d…. One copy: consistency is easy, but if it happens to be down everybody is out of the water, and if people are remote then may pay horrid communication costs. It handles turning raw gossip into the right internal state and dealing with ring changes, i.e., transferring data to new replicas. Splitting writes from different individual “modules” in the application (that is, groups of independent tables) to different nodes in the cluster. We explore the impact of partitions below. Note that for scalability there can be clusters of master-slave nodes handling different tables, but that will be discussed later). Planning a cluster deployment. https://stackoverflow.com/questions/3736969/master-master-vs-master-slave-database-architecture. Many nodes are categorized as a data center. There are following components in the Cassandra; 1. In extremely un-optimized workloads with high concurrency, directing all writes to a single RAC node and load-balancing only the reads. In a master slave-based HA system where master and slaves run in different compute nodes (because there is a limit of vertical scalability), the Split Brain syndrome is a curse which does not have a good solution. If nodes are changing position on the ring, "pending ranges" are associated with their destinations in TokenMetadata and these are also written to. The topics related to Cassandra Architecture have extensively been covered in our 'Cassandra' course. Database internals. This is essentially flawed. Prerequisites. As required by consistency level, additional nodes may be sent digest commands, asking them to perform the read locally but send back the digest only. Note the Memory and Disk Part. Apache Cassandra solves many interesting problems to provide a scalable, distributed, fault tolerant database. Let us explore the Cassandra architecture in the next section. This is also known as “application partitioning” (not to be confused with database table partitions). Since then, I’ve had the opportunity to work as a database architect and administrator with all Oracle versions up to and including Oracle 12.2. Users can also leverage the same MongoDB query language, data model, scaling, security, and operational tooling across different applications, each pow… Cassandra CLI is a useful tool for Cassandra administrators. 2. Cassandra has a peer-to-peer (or “masterless”) distributed “ring” architecture that is elegant, easy to set up, and maintain.In Cassandra, all nodes are the same; there is … In master-slave, the master is the one which generally does the write and reads can be distributed across master and slave; the slave is like a hot standby. Since SSTable is a different file and Commit log is a different file and since there is only one arm in a magnetic disk, this is the reason why the main guideline is to configure Commit log in a different disk (not even partition and SStable (data directory)in a separate disk. When Memtables are flushed, a check is scheduled to see if a compaction should be run to merge SSTables. The point is, these two goals often conflict, so you’ll need to try to balance them. It is technically a CP system. Cassandra performs very well on both spinning hard drives and solid state disks. The reason for this kind of Cassandra’s architecture was that the hardware failure can occur at any time. I’ll start this blog post with a quick disclaimer. On the data node, ReadVerbHandler gets the data from CFS.getColumnFamily, CFS.getRangeSlice, or CFS.search for single-row reads, seq scans, and index scans, respectively, and sends it back as a ReadResponse. The relation between PRIMARY Key and PARTITION KEY. 4. In case of failure data stored in another node can be used. Cluster− A cluster is a component that contains one or more data centers. For these reasons, compaction is needed. Apache Spark: core concepts, architecture and internals 03 March 2016 on Spark , scheduling , RDD , DAG , shuffle This post covers core concepts of Apache Spark such as RDD, DAG, execution workflow, forming stages of tasks and shuffle implementation and also describes architecture and main components of Spark Driver. 4. replicas of each key range. Cassandra uses the PARTITION COLUMN Key value and feeds it a hash function which tells which of the bucket the row has to be written to. https://blog.timescale.com/scaling-partitioning-data-postgresql-10-explained-cd48a712a9a1, There is another part to this, and it relates to the master-slave architecture which means the master is the one that writes and slaves just act as a standby to replicate and distribute reads. — https://www.cockroachlabs.com/docs/stable/strong-consistency.html, The main difference is that since CockroachDB does not have Google infrastructure to implement TrueTime API to synchronize the clocks across the distributed system, the consistency guarantee it provides is known as Serializability and not Linearizability (which Spanner provides). Here is an interesting Stack Overflow QA that sums up quite easily one main trade-off with these two type of architectures. If read repair is (probabilistically) enabled (depending on read_repair_chance and dc_local_read_repair_chance), remaining nodes responsible for the row will be sent messages to compute the digest of the response. There are two broad types of HA Architectures Master -slave and Masterless or master-master architecture. Configuration file is parsed by DatabaseDescriptor (which also has all the default values, if any) Thrift generates an API interface in Cassandra.java; the implementation is CassandraServer, and CassandraDaemon ties it together (mostly: handling commitlog replay, and setting up the Thrift plumbing) CassandraServer turns thrift requests into the internal equivalents, then StorageProxy does the actual work, then CassandraServer … Every write operation is written to the commit log. Partition key: Cassandra's internal data representation is large rows with a unique key called row key. Figure 3: Cassandra's Ring Topology MongoDB Cassandra is a great NoSQL product. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. When we need to distribute the data across multi-nodes for data availability (read data safety), the writes have to be replicated to that many numbers of nodes as Replication Factor. The purist answer is “no” because partitions can happen and in fact have happened at Google, and during (some) partitions, Spanner chooses C and forfeits A. This blog gives the internals of LSM if you are interested. MessagingService handles connection pooling and running internal commands on the appropriate stage (basically, a threaded executorservice). Obviously, this is done by a third node which is neither master or slave as it can only know if the master is gone down or not (NW down is also master down). Please see above where I mentioned the practical limits of a pseudo master-slave system like shared disk systems). Before we leave this, for those curious you can see here the mechanism from Oracle RAC to tackle the split-brain (all master-slave architectures this will crop up but never in a true masterless system)-where they assume the common shared disk is always available from all cluster; I don’t know in depth the RAC structure, but looks like a classical distributed computing fallacy or a single point of failure if not configured redundantly; which on further reading, they are recommending to cover this part. Developers / Data architects. Cassandra's Internal Architecture 2.1. Technically, Oracle RAC can scale writes and reads together when adding new nodes to the cluster, but attempts from multiple sessions to modify rows that reside in the same physical Oracle block (the lowest level of logical I/O performed by the database) can cause write overhead for the requested block and affect write performance. Multiple CompactionStrategies exist. (Cassandra does not do a Read before a write, so there is no constraint check like the Primary key of relation databases, it just updates another row), The partition key has a special use in Apache Cassandra beyond showing the uniqueness of the record in the database -https://www.datastax.com/dev/blog/the-most-important-thing-to-know-in-cassandra-data-modeling-the-primary-key. ), deployment considerations, and performance tuning. Cassandra developers, who work on the Cassandra source code, should refer to the Architecture Internals developer documentation for a more detailed overview. Mem-table− A mem-table is a memory-resident data structure. Snitches. We have skipped some parts here. This works particularly well for HDDs. To have a good read performance/fast query we need data for a query in one partition read one node.There is a balance between write distribution and read consolidation that you need to achieve, and you need to know your data and query to know that. Commit log is used for crash recovery. 5. Don’t model around relations. {"serverDuration": 138, "requestCorrelationId": "50f7bd6f5ac860cb"}, https://issues.apache.org/jira/browse/CASSANDRA-833, http://www.datastax.com/dev/blog/leveled-compaction-in-apache-cassandra, http://www.datastax.com/dev/blog/when-to-use-leveled-compaction, http://www.cs.cornell.edu/home/rvr/papers/flowgossip.pdf, http://www.eecs.harvard.edu/~mdw/papers/seda-sosp01.pdf, http://www.allthingsdistributed.com/2007/10/amazons_dynamo.html, annotated and compared to Apache Cassandra 2.0, https://c.statcounter.com/9397521/0/fe557aad/1/, Configuration file is parsed by DatabaseDescriptor (which also has all the default values, if any), Thrift generates an API interface in Cassandra.java; the implementation is CassandraServer, and CassandraDaemon ties it together (mostly: handling commitlog replay, and setting up the Thrift plumbing), CassandraServer turns thrift requests into the internal equivalents, then StorageProxy does the actual work, then CassandraServer turns the results back into thrift again, CQL requests are compiled and executed through. A single logical database is spread across a cluster of nodes and thus the need to spread data evenly amongst all participating nodes. Reading and Consistency. This directly takes us to the evolution of NoSQL databases. Any node can be down. However, it is a waste of disk space. Documentation for developers and administrators on installing, configuring, and using the features and capabilities of Apache Cassandra scalable open source NoSQL database. Cassandra Architecture. The idea of dividing work into "stages" with separate thread pools comes from the famous SEDA paper: Crash-only design is another broadly applied principle. The Failure Detector is the only component inside Cassandra (only the primary gossip class can mark a node UP besides) to do so. http://oracleinaction.com/voting-disk/. CREATE TABLE rank_by_year_and_name ( PRIMARY KEY ((race_year, race_name), rank) ); For writes to be distributed and scaled the partition key should be chosen so that it distributes writes in a balanced way across all nodes. Another from a blog referred from Google Cloud Spanner page which captures sort of the essence of this problem. Installing Vital information about successfully deploying a Cassandra cluster. Commit log has the data of the commit also and is used for persistence and recovering in scenarios like power-off before flushing to SSTable. More specifically a ParitionKey should be unique and all values of those are needed in the WHERE clause. Yes, you are right; and that is what I wanted to highlight. For the sake of brevity and clarity the ‘read path’ description below ignores consistency level and explains the ‘read path’ using a single local coordinator and a single replica node. Cross-datacenter writes are not sent directly to each replica; instead, they are sent to a single replica with a parameter in MessageOut telling that replica to forward to the other replicas in that datacenter; those replicas will respond diectly to the original coordinator. Cassandra uses a log-structured storage system, meaning that it will buffer writes in memory until it can be persisted to disk in one large go. Writes are serviced using the Raft consensus algorithm, a popular alternative to Paxos. We use MySQL to power our website, which allows us to serve millions of students every month, but is difficult to scale up — we need our database to handle more writes than a single machine can process. Cockroach DB is an open source in-premise database of Cloud Spanner -that is Highly Available and strongly Consistent that uses Paxos type algorithm. Cassandra. Suppose there are three nodes in a Cassandra cluster. But don’t you think it is common sense that if a query read has to touch all the nodes in the NW it will be slow. I used to work in a project with a big Oracle RAC system, and have seen the problems related to maintaining it in the context of the data that scaled out with time. Q. how data is replicated, how data is written to and read from disk, etc. https://www.datastax.com/dev/blog/the-most-important-thing-to-know-in-cassandra-data-modeling-the-primary-key, A more detailed example of modelling the Partition key along with some explanation of how CAP theorem applies to Cassandra with tunable consistency is described in part 2 of this series, https://medium.com/techlogs/using-apache-cassandra-a-few-things-before-you-start-ac599926e4b8, https://medium.com/stashaway-engineering/running-a-lagom-microservice-on-akka-cluster-with-split-brain-resolver-2a1c301659bd, single point of failure if not configured redundantly, https://www.datastax.com/wp-content/uploads/2012/09/WP-DataStax-MultiDC.pdf, https://www.cockroachlabs.com/docs/stable/strong-consistency.html, https://blog.timescale.com/scaling-partitioning-data-postgresql-10-explained-cd48a712a9a1, each replication set being a master-slave, http://cassandra.apache.org/doc/4.0/operating/hardware.html, https://github.com/scylladb/scylla/wiki/SSTable-compaction-and-compaction-strategies, ttps://stackoverflow.com/questions/32867869/how-cassandra-chooses-the-coordinator-node-and-the-replication-nodes, http://db.geeksinsight.com/2016/07/19/cassandra-for-oracle-dbas-part-2-three-things-you-need-to-know/, Understanding the Object-Oriented Programming, preventDefault vs. stopPropagation vs. stopImmediatePropagation, How to Use WireMock with JUnit 5 in Kotlin Spring Boot Application, Determining the effectiveness of Selective Memoization to defeat ReDoS. If we are reading a slice of columns, we use the row-level column index to find where to start reading, and deserialize block-at-a-time (where "block" is the group of columns covered by a single index entry) so we can handle the "reversed" case without reading vast amounts into memory, If we are reading a group of columns by name, we use the column index to locate each column, If compression is enabled, the block that the requested data lives in must be uncompressed, Data from Memtables and SSTables is then merged (primarily in CollationController), The column readers provide an Iterator interface, so the filter can easily stop when it's done, without reading more columns than necessary, Since we need to potentially merge columns from multiple SSTable versions, the reader iterators are combined through a ReducingIterator, which takes an iterator of uncombined columns as input, and yields combined versions as output, If row caching is enabled, the row cache is updated in ColumnFamilyStore.getThroughCache(). https://www.google.co.in/search?rlz=high+availabillity+master+slave+and+the+split+brain+syndrome. Cassandra was designed to ful ll the storage needs of the Inbox Search problem. Understand replication 2.3. This technique, of keeping sorted files and merging them, is a well-known one and often called Log-Structured Merge (LSM) tree. Making this concurrency-safe without blocking writes or reads while we remove the old SSTables from the list and add the new one is tricky. CompactionManager manages the queued tasks and some aspects of compaction. 1. (More accurately, Oracle RAC or MongoDB Replication Sets are not exactly limited by only one master to write and multiple slaves to read from; but either use a shared storage and multiple masters -slave sets to write and read to, in case of Oracle RAC; and similar in case of MongoDB uses multiple replication sets with each replication set being a master-slave combination, but not using shared storage like Oracle RAC. Isn’t the master-master more suitable for today’s web cause it’s like Git, every unit has the whole set of data and if one goes down, it doesn’t quite matter. The closest node (as determined by proximity sorting as described above) will be sent a command to perform an actual data read (i.e., return data to the co-ordinating node). It uses these row key values to distribute data across cluster nodes. Read repair, adjustable consistency levels, hinted handoff, and other concepts are discussed there. Here is a quote from a better expert. Master Slave: consistency is not too difficult because each piece of data has exactly one owning master. Hence, you should maintain multiple copies of the voting disks on separate disk LUNs so that you eliminate a Single Point of Failure (SPOF) in your Oracle 11g RAC configuration. But then what do you do if you can’t see that master, some kind of postponed work is needed. After returning the most recent value, Cassandra performs a read repair in the background to update the stale values. Database scaling is done via sharding, the key thing is if sharding is automatic or manual. Architecture Overview Cassandra’s architecture is responsible for its ability to scale, perform, and offer continuous uptime.

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