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cassandra architecture internals

Splitting writes from different individual “modules” in the application (that is, groups of independent tables) to different nodes in the cluster. This is the most essential skill that one needs when doing modeling for Cassandra. 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). Planning a cluster deployment. In general, if you are writing a lot of data to a PostgreSQL table, at some point you’ll need partitioning. 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. 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. SSTable flush happens periodically when memory is full. 3 days. Data center− It is a collection of related nodes. We have skipped some parts here. It provides near real-time performance for designed queries and enables high availability with linear scale growth as it uses the eventually consistent paradigm. For single-row requests, we use a QueryFilter subclass to pick the data from the Memtable and SSTables that we are looking for. Data … Data Partitioning- Apache Cassandra is a distributed database system using a shared nothing architecture. By separating the commitlog from the data directory, writes can benefit from sequential appends to the commitlog without having to seek around the platter as reads request data from various SSTables on disk. In order to understand Cassandra's architecture it is important to understand some key concepts, data structures and algorithms frequently used by Cassandra. We needed Oracle support and also an expert in storage/SAN networking to balance disk usage. After commit log, the data will be written to the mem-table. Many nodes are categorized as a data center. SimpleStrategy just puts replicas on the next N-1 nodes in the ring. Compaction is the process of reading several SSTables and outputting one SSTable containing the merged, most recent, information. NetworkTopologyStrategy allows the user to define how many replicas to place in each datacenter, and then takes rack locality into account for each DC – we want to avoid multiple replicas on the same rack, if possible. Cockroach DB maybe something to see as it gets more stable; Scalability — Application Sharding and Auto-Sharding. 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. 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. In case of failure data stored in another node can be used. Q. A useful resource for anyone new to Cassandra. Multiple CompactionStrategies exist. I’ll start this blog post with a quick disclaimer. A Cassandra installation can be logically divided into racks and the specified snitches within the cluster that determine the best node and rack for replicas to be stored. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. StorageProxy gets the nodes responsible for replicas of the keys from the ReplicationStrategy, then sends RowMutation messages to them. The reason for this kind of Cassandra’s architecture was that the hardware failure can occur at any time. 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. You can see how the COMPOSITE PARTITION KEY is modelled so that writes are distributed across nodes and reads for particular state lands in one partition. Cassandra CLI is a useful tool for Cassandra administrators. 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. This directly takes us to the evolution of NoSQL databases., 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. If there is a cache hit, the coordinator can be responded to immediately. CREATE TABLE user_videos ( PRIMARY KEY (userid, added_date, videoid)); Example 3: COMPOSITE PARTITION KEY ==(race_year, race_name). 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 Also, updates to rows are new insert’s in another SSTable with a higher timestamp and this also has to be reconciled with different SSTables for reading. -I’ve heard about two kind of database architectures. 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. Users can also leverage the same MongoDB query language, data model, scaling, security, and operational tooling across different applications, each pow… Auto-sharding is a key feature that ensures scalability without complexity increasing in the code. 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. Through the use of pluggable storage engines, MongoDB can be extended with new capabilities and configured for optimal use of specific hardware architectures. I’m what you would call a “born and raised” Oracle DBA. This can result is a lot of wasted space in overwrite-intensive workloads. 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. Topics about the Cassandra database. 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. 1. A Primary key should be unique. 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. Database internals. 'Tis the season to get all of your urgent and demanding Cassandra questions answered live! Cassandra. Commit log is used for crash recovery. (Streaming is for when one node copies large sections of its SSTables to another, for bootstrap or relocation on the ring.) At a 10000 foot level Cassa… 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. If some of the nodes are responded with an out-of-date value, Cassandra will return the most recent value to the client. Depending on the query type, the read commands will be SliceFromReadCommands, SliceByNamesReadCommands, or a RangeSliceCommand. Cassandra developers, who work on the Cassandra source code, should refer to the Architecture Internals developer documentation for a more detailed overview. Partition key: Cassandra's internal data representation is large rows with a unique key called row key. Mem-table− A mem-table is a memory-resident data structure. 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. 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. Although you can scale read performance easily by adding more cluster nodes, scaling write performance is a more complex subject. 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. Also when there are multiple nodes, which node should a client connect to? AbstractReplicationStrategy controls what nodes get secondary, tertiary, etc. There are a large number of Cassandra metrics out of which important and relevant metrics can provide a good picture of the system. Suppose there are three nodes in a Cassandra cluster. Cassandra monitoring is essential to get insight into the database internals. Audience. Understanding the architecture. 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). This position is added to the key cache. 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. This would mean that read query may have to read multiple SSTables. 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. Model around your queries. 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. Cassandra was designed to ful ll the storage needs of the Inbox Search problem. Bring portable devices, which may need to operate disconnected, into the picture and one copy won’t cut it. Understand replication 2.3. With this disclaimer -Oracle RAC is said to be masterless, I will consider it to be a pseudo-master-slave architecture as there is a shared ‘master’ disk that is the basis of its architecture. Every write operation is written to the commit log. ClusterThe cluster is the collection of many data centers. Back on the coordinator node, responses from replicas are handled: If a replica fails to respond before a configurable timeout, a, If responses (data and digests) do not match, a full data read is performed against the contacted replicas in order to guarantee that the most recent data is returned, Once retries are complete and digest mismatches resolved, the coordinator responds with the final result to the client, At any point if a message is destined for the local node, the appropriate piece of work (data read or digest read) is directly submitted to the appropriate local stage (see. 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. Understand the System keyspace 2.5. 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. 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). To locate the data row's position in SSTables, the following sequence is performed: The key cache is checked for that key/sstable combination. (Here is a gentle introduction which seems easier to follow than others (I do not know how it works)). 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., Apache Cassandra does not use Paxos yet has tunable consistency (sacrificing availability) without complexity/read slowness of Paxos consensus. It introduces all the important concepts needed to understand Cassandra, including enough coverage of internal architecture so you can make optimal decisions. It handles turning raw gossip into the right internal state and dealing with ring changes, i.e., transferring data to new replicas. More specifically a ParitionKey should be unique and all values of those are needed in the WHERE clause. Storage engine If it’s good to minimize the number of partitions that you read from, why not put everything in a single big partition? Cluster wide operations track node membership, d…. Storage engines can be mixed on same replica set or sharded cluster. We explore the impact of partitions below. Let us now see how this automatic sharding is done by Cassandra and what it means to data Modelling. I am however no expert. 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. Database internals. It also covers CQL (Cassandra Query Language) in depth, as well as covering the Java API for writing Cassandra clients. Figure 3: Cassandra's Ring Topology MongoDB Cassandra's Internal Architecture 2.1. 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). If nodes are changing position on the ring, "pending ranges" are associated with their destinations in TokenMetadata and these are also written to. LeveledCompactionStrategy provides stricter guarantees at the price of more compaction i/o; see. Any node can act as the coordinator, and at first, requests will be sent to the nodes which your driver knows about….The coordinator only stores data locally (on a write) if it ends up being one of the nodes responsible for the data’s token range -- This is essentially flawed. Note that Delete’s are like updates but with a marker called Tombstone and are deleted during compaction. This is one of the reasons that Cassandra does not like frequent Delete. 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. 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. How is … If the row cache is enabled, it is first checked for the requested row (in ColumnFamilyStore.getThroughCache). Writes are serviced using the Raft consensus algorithm, a popular alternative to Paxos.|stats. 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). Cassandra is a great NoSQL product. When performing atomic batches, the mutations are written to the batchlog on two live nodes in the local datacenter. About Apache Cassandra. 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? It uses these row key values to distribute data across cluster nodes. The short answer is “no” technically, but “yes” in effect and its users can and do assume CA. 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. The way to minimize partition reads is to model your data to fit your queries. The row cache will contain the full partition (storage row), which can be trimmed to match the query. 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. Powered by a free Atlassian Confluence Open Source Project License granted to Apache Software Foundation. Why doesn’t PostgreSQL naturally scale well? (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 - The flush from Memtable to SStable is one operation and the SSTable file once written is immutable (not more updates). The relation between PRIMARY Key and PARTITION KEY. Stages are set up in StageManager; currently there are read, write, and stream stages. 2. The topics related to Cassandra Architecture have extensively been covered in our 'Cassandra' course. It is always written in append mode and read-only on startup. 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. The claim to speed over HBase is the fact that Cassandra uses its own distributed filesystem called CFS over HDFS. The point is, these two goals often conflict, so you’ll need to try to balance them. Starting in 1.2, each node may have multiple Tokens. based on "Efficient reconciliation and flow control for anti-entropy protocols:", based on "The Phi accrual failure detector:". Here is a snippet from the net. Understand and tune consistency 2.4. Throughout my career, I’ve delivered a lot of successful projects using Oracle as the relational database componen…. Note that for scalability there can be clusters of master-slave nodes handling different tables, but that will be discussed later). 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. 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. Voting disk needs to be mirrored, should it become unavailable, cluster will come down. This approach significantly reduces developer and operational complexity compared to running multiple databases. It is technically a CP system. - We perform manual reference counting on sstables during reads so that we know when they are safe to remove, e.g., ColumnFamilyStore.getSSTablesForKey. There are two broad types of HA Architectures Master -slave and Masterless or master-master architecture. CREATE TABLE videos (…PRIMARY KEY (videoid)); Example 2: PARTITION KEY == userid, rest of PRIMARY keys are Clustering keys for ordering/sortig the columns. But then what do you do if you can’t see that master, some kind of postponed work is needed. It is included for backwards compatibility. Commit LogEvery write operation is written to Commit Log. A single logical database is spread across a cluster of nodes and thus the need to spread data evenly amongst all participating nodes. 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 … 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 synthesis of well known techniques to achieve scalability and availability. You would end up violating Rule #1, which is to spread data evenly around the cluster. 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. First, Google runs its own private global network. In Cassandra, nodes in a cluster act as replicas for a given piece of data. 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. On the destination node, RowMutationVerbHandler calls, When a Memtable is full, it is asynchronously sorted and written out as an SSTable by ColumnFamilyStore.switchMemtable, "Fullness" is monitored by MeteredFlusher; the goal is to flush quickly enough that we don't OOM as new writes arrive while we still have to hang on to the memory of the old memtable during flush. 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. ), deployment considerations, and performance tuning. …. 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. It has a ring-type architecture, that is, its nodes are logically distributed like a ring. Cassandra Community Webinar: Apache Cassandra Internals. 4. This technique, of keeping sorted files and merging them, is a well-known one and often called Log-Structured Merge (LSM) tree. One main part is Replication. My first job, 15 years ago, had me responsible for administration and developing code on production Oracle 8 databases. StorageService is kind of the internal counterpart to CassandraDaemon. The set of SSTables to read data from are narrowed at various stages of the read by the following techniques: If a row tombstone is read in one SSTable and its timestamp is greater than the max timestamp in a given SSTable, that SSTable can be ignored, If we're requesting column X and we've read a value for X from an SSTable at time T1, any SSTables whose maximum timestamp is less than T1 can be ignored, If a slice is requested and the min and max column names for a given SSTable do not fall within the slice, that SSTable can be ignored. 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. Primary replica is always determined by the token ring (in TokenMetadata) but you can do a lot of variation with the others. See the wikipedia article for more. 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. After returning the most recent value, Cassandra performs a read repair in the background to update the stale values. —, 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). 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. Please see above where I mentioned the practical limits of a pseudo master-slave system like shared disk systems).

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