Cassandra architecture & internals; CQL (Cassandra Query Language) Data modeling in CQL; Using APIs to interact with Cassandra; Duration. Apache Cassandra — The minimum internals you need to know Part 1: Database Architecture — Master-Slave and Masterless and its impact on HA and Scalability There are two broad types of HA Architectures Master -slave and Masterless or master-master architecture. By manual, I mean that application developer do the custom code to distribute the data in code — application-level sharding. Don’t model around objects. 4. Database scaling is done via sharding, the key thing is if sharding is automatic or manual. The Split-brain syndrome — if there is a network partition in a cluster of nodes, then which of the two nodes is the master, which is the slave? Let us now see how this automatic sharding is done by Cassandra and what it means to data Modelling. 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. Apache Cassandra solves many interesting problems to provide a scalable, distributed, fault tolerant database., 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. (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. 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. Let us explore the Cassandra architecture in the next section. {"serverDuration": 138, "requestCorrelationId": "50f7bd6f5ac860cb"},,,,,,, annotated and compared to Apache Cassandra 2.0,, Configuration file is parsed by DatabaseDescriptor (which also has all the default values, if any), Thrift generates an API interface in; 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. This is the most essential skill that one needs when doing modeling for Cassandra. Partition key: Cassandra's internal data representation is large rows with a unique key called row key. 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. Before that let us go shallowly into — Cassandra Read Path, For reads to be NOT distributed across multiple nodes (that is fetched and combine from multiple nodes) a read triggered from a client query should fall in one partition (forget replication for simplicity), This is illustrated beautifully in the diagram below. Mem-table− A mem-table is a memory-resident data structure. Primary replica is always determined by the token ring (in TokenMetadata) but you can do a lot of variation with the others. Spanner is not running over the public Internet — in fact, every Spanner packet flows only over Google-controlled routers and links (excluding any edge links to remote clients). 3. The course covers important topics such as internal architecture for making sound decisions, CQL (Cassandra Query Language) as well as Java APIs for writing Cassandra clients. Mem-tableAfter data written in C… Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra was designed to ful ll the storage needs of the Inbox Search problem. + others. (Here is a gentle introduction which seems easier to follow than others (I do not know how it works)). Through the use of pluggable storage engines, MongoDB can be extended with new capabilities and configured for optimal use of specific hardware architectures. First, Google runs its own private global network. I am however no expert. It comes down to the performance gap between RAM and disk. Data … Cassandra Cassandra has a peer-to-peer ring based architecture that can be deployed across datacenters. Every write operation is written to the commit log. A digest read will take the full cost of a read internally on the node (CPU and in particular disk), but will avoid taxing the network. 'Tis the season to get all of your urgent and demanding Cassandra questions answered live! 3 days. It also slows down reads: different SSTables can hold different columns of the same row, so a query might need to read from multiple SSTables to compose its result. Important topics for understanding Cassandra. Prerequisites. 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. It's a good example of how to implement a Cassandra client and CLI internals help us to develop custom Cassandra clients or … Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. 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. Depends on where the NW partition happens; It seems easy to solve, but unless there is some guarantee that the third node/common node has 100% connection reliability with other nodes, it is hard to resolve. Any node can be down. If it’s good to minimize the number of partitions that you read from, why not put everything in a single big partition? Database internals. NodeNode is the place where data is stored. How is … Cassandra Community Webinar: Apache Cassandra Internals. Q. Cassandra's distribution is closely related to the one presented in Amazon's Dynamo paper. Planning a cluster deployment. ( It uses Paxos only for LWT. 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. Audience. In Cassandra, nodes in a cluster act as replicas for a given piece of data. My first job, 15 years ago, had me responsible for administration and developing code on production Oracle 8 databases. how data is replicated, how data is written to and read from disk, etc. Some classes have misleading names, notably ColumnFamily (which represents a single row, not a table of data) and, prior to 2.0, Table (which was renamed to Keyspace). We were using pgpool-2 and this was I guess one of the bugs that bit us. If nodes are changing position on the ring, "pending ranges" are associated with their destinations in TokenMetadata and these are also written to. However, when using spinning disks, it’s important that the commitlog (commitlog_directory) be on one physical disk (not simply a partition, but a physical disk), and the data files (data_file_directories) be set to a separate physical disk. The main problem happens when there is an automatic switchover facility for HA when a master dies. So, the problem compounds as you index more columns. After commit log, the data will be written to the mem-table. …. The short answer is “no” technically, but “yes” in effect and its users can and do assume CA. The text is quite engaging and enjoyable to read. Cluster wide operations track node membership, d…. Spanner claims to be consistent and available Despite being a global distributed system, Spanner claims to be consistent and highly available, which implies there are no partitions and thus many are skeptical.1 Does this mean that Spanner is a CA system as defined by CAP?, Apache Cassandra does not use Paxos yet has tunable consistency (sacrificing availability) without complexity/read slowness of Paxos consensus. Here is a quote from a better expert. There are following components in the Cassandra; 1. DS201: DataStax Enterprise 6 Foundations of Apache Cassandra™ In this course, you will learn the fundamentals of Apache Cassandra™, its distributed architecture, and how data is stored. In both cases, Cassandra’s sorted immutable SSTables allow for linear reads, few seeks, and few overwrites, maximizing throughput for HDDs and lifespan of SSDs by avoiding write amplification. Compaction is the process of reading several SSTables and outputting one SSTable containing the merged, most recent, information. To locate the data row's position in SSTables, the following sequence is performed: The key cache is checked for that key/sstable combination. In-Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are If there is a cache hit, the coordinator can be responded to immediately. Voting disk needs to be mirrored, should it become unavailable, cluster will come down. If some of the nodes are responded with an out-of-date value, Cassandra will return the most recent value to the client. 5. I’m what you would call a “born and raised” Oracle DBA. Since these row keys are used to partition data, they as called partition keys. The key components of Cassandra are as follows − 1. The way to minimize partition reads is to model your data to fit your queries. 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. 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. 2010-03-17 cassandra In my previous post, I discussed how writes happen in Cassandra and why they are so fast.Now we’ll look at reads and learn why they are slow. 1. Here is an interesting Stack Overflow QA that sums up quite easily one main trade-off with these two type of architectures. When performing atomic batches, the mutations are written to the batchlog on two live nodes in the local datacenter. When Memtables are flushed, a check is scheduled to see if a compaction should be run to merge SSTables. SimpleStrategy just puts replicas on the next N-1 nodes in the ring. 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. 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. We needed Oracle support and also an expert in storage/SAN networking to balance disk usage. It uses the same function on the WHERE Column key value of the READ Query which also gives exactly the same node where it has written the row. Developers / Data architects. There are many solutions to this problem, but these can be complex to run or require extensive refactoring of your application’s SQL queries,, These type of scenarios are common and a lot of instances can be found of SW trying to fix this. Documentation for developers and administrators on installing, configuring, and using the features and capabilities of Apache Cassandra scalable open source NoSQL database. This is one of the reasons that Cassandra does not like frequent Delete. However, due to the complexity of the distributed database, there is additional safety (read complexity) added like gc_grace seconds to prevent Zombie rows. Data Partitioning- Apache Cassandra is a distributed database system using a shared nothing architecture. 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. 3. Master Slave: consistency is not too difficult because each piece of data has exactly one owning master. This is called. 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. Commit LogEvery write operation is written to Commit Log. The point is, these two goals often conflict, so you’ll need to try to balance them. These SSTables might contain outdated data — e.g., different SSTables might contain both an old value and new value of the same cell, or an old value for a cell later deleted. LeveledCompactionStrategy provides stricter guarantees at the price of more compaction i/o; see. See the wikipedia article for more. (Streaming is for when one node copies large sections of its SSTables to another, for bootstrap or relocation on the ring.) The internal commands are defined in StorageService; look for, Configuration for the node (administrative stuff, such as which directories to store data in, as well as global configuration, such as which global partitioner to use) is held by DatabaseDescriptor. This is required background material: Cassandra's on-disk storage model is loosely based on sections 5.3 and 5.4 of, Facebook's Cassandra team authored a paper on Cassandra for LADIS 09, which has now been. 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. 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. This approach significantly reduces developer and operational complexity compared to running multiple databases. Monitoring is a must for production systems to ensure optimal performance, alerting, troubleshooting, and debugging. Cassandra. Please see above where I mentioned the practical limits of a pseudo master-slave system like shared disk systems). 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. Data CenterA collection of nodes are called data center. Cassandra is a decentralized distributed database No master or slave nodes No single point of failure Peer-Peer architecture Read / write to any available node Replication and data redundancy built into the architecture Data is eventually consistent across all cluster nodes Linearly (and massively) scalable Multiple Data Center support built in – a single cluster can span geo locations Adding or … Many people may have seen the above diagram and still missed few parts. - StorageProxy gets the nodes responsible for replicas of the keys from the ReplicationStrategy, then sends RowMutation messages to them. Cassandra provides this partitioner for ordered partitioning. 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 … Node− It is the place where data is stored. Cassandra performs very well on both spinning hard drives and solid state disks. This is well known phenomena and why RAC-Aware applications are a real thing in the real world. However, it is a waste of disk space. Cluster− A cluster is a component that contains one or more data centers. If you want to get an intuition behind compaction and how relates to very fast writes (LSM storage engine) and you can read this more. based on "Efficient reconciliation and flow control for anti-entropy protocols:", based on "The Phi accrual failure detector:". CREATE TABLE videos (…PRIMARY KEY (videoid)); Example 2: PARTITION KEY == userid, rest of PRIMARY keys are Clustering keys for ordering/sortig the columns. comfortable with Java programming language; comfortable in Linux environment (navigating command line, running commands) Lab environment. Commit log is used for crash recovery. We have skipped some parts here. Understand how requests are coordinated 2.2. 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. We will discuss two parts here; first, the database design internals that may help you compare between database’s, and second the main intuition behind auto-sharding/auto-scaling in Cassandra, and how to model your data to be aligned to that model for the best performance. Why doesn’t PostgreSQL naturally scale well? Cassandra uses a synthesis of well known techniques to achieve scalability and availability. For single-row requests, we use a QueryFilter subclass to pick the data from the Memtable and SSTables that we are looking for. But if the data is sufficiently large that we can’t fit all (similarly fixed-size) pages of our index in memory, then updating a random part of the tree can involve significant disk I/O as we read pages from disk into memory, modify in memory, and then write back out to disk (when evicted to make room for other pages). The flush from Memtable to SStable is one operation and the SSTable file once written is immutable (not more updates). On the data node, ReadVerbHandler gets the data from CFS.getColumnFamily, CFS.getRangeSlice, or for single-row reads, seq scans, and index scans, respectively, and sends it back as a ReadResponse. Although you can scale read performance easily by adding more cluster nodes, scaling write performance is a more complex subject. 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. Reading and Consistency. Yes, you are right; and that is what I wanted to highlight. (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 - Cassandra CLI is a useful tool for Cassandra administrators. Strong knowledge in NoSQL schema ... Report job. Database internals. 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). 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. Data center− It is a collection of related nodes. See also. Another from a blog referred from Google Cloud Spanner page which captures sort of the essence of this problem. It covers two parts, the disk I/O part (which I guess early designers never thought will become a bottleneck later on with more data-Cassandra designers knew fully well this problem and designed to minimize disk seeks), and the other which is more important touches on application-level sharding. Some of the features of Cassandra architecture are as follows: Cassandra is designed such that it has no master or slave nodes. Peer-to-peer, distributed system in which all nodes are alike hence reults in read/write anywhere design. Many nodes are categorized as a data center. In case of failure data stored in another node can be used. Contains coverage of data modeling in Cassandra, CQL (Cassandra Query Language), Cassandra internals (e.g. If the local datacenter contains multiple racks, the nodes will be chosen from two separate racks that are different from the coordinator's rack, when possible. MessagingService handles connection pooling and running internal commands on the appropriate stage (basically, a threaded executorservice). Sometimes, for a single-column family, ther… Figure 3: Cassandra's Ring Topology MongoDB Cassandra developers, who work on the Cassandra source code, should refer to the Architecture Internals developer documentation for a more detailed overview. Understand the System keyspace 2.5. Cassandra Architecture. This would mean that read query may have to read multiple SSTables. Architecture Overview Cassandra’s architecture is responsible for its ability to scale, perform, and offer continuous uptime. Bring portable devices, which may need to operate disconnected, into the picture and one copy won’t cut it. But then what do you do if you can’t see that master, some kind of postponed work is needed. 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. The Failure Detector is the only component inside Cassandra (only the primary gossip class can mark a node UP besides) to do so. Commit log− The commit log is a crash-recovery mechanism in Cassandra. With the limitations for pure write scale-out, many Oracle RAC customers choose to split their RAC clusters into multiple “services,” which are logical groupings of nodes in the same RAC cluster., 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,,, single point of failure if not configured redundantly,,,, each replication set being a master-slave,,, ttps://,, 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. The primary index is scanned, starting from the above location, until the key is found, giving us the starting position for the data row in the sstable. The topics related to Cassandra Architecture have extensively been covered in our 'Cassandra' course. It is technically a CP system. A Primary key should be unique. Trouble is it very hard to preserve absolute consistency. It is not just a Postgres problem, a general google search (below) on this should throw up many problems most such software, Postgres, MySQL, Elastic Search etc. 3. There are a large number of Cassandra metrics out of which important and relevant metrics can provide a good picture of the system.
2020 cassandra architecture internals