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YugabyteDB is comprised of 2 logical layers, YQL and DocDB.
YQL is the upper layer that has the API specific aspects - for example, the server-side implementation of the YEDIS/YCQL/YSQL APIs, and the corresponding query/command compilation and run-time (data type representations, built-in operations and more).
DocDB, a distributed document store, is a highly available, distributed system with strong write consistency, tunable read consistency, and an advanced log-structured row/document-oriented storage. It includes several optimizations for handling ever-growing datasets efficiently.
In terms of the traditional CAP theorem, YugabyteDB is a CP database (consistent and partition tolerant), but achieves very high availability. The architectural design of Yugabyte is similar to Google Cloud Spanner, which is also a CP system. The description about Spanner is just as valid for YugabyteDB. The key takeaway is that no system provides 100% availability, so the pragmatic question is whether or not the system delivers availability that is so high that most users no longer have to be concerned about outages. For example, given there are many sources of outages for an application, if YugabyteDB is an insignificant contributor to its downtime, then users are correct to not worry about it.
A YugabyteDB universe, is a group of nodes (VMs, physical machines or containers) that collectively function as a highly available and resilient database.
The universe can be deployed in a variety of configurations depending on business requirements, and latency considerations. Some examples:
- Single availability zone (AZ/rack/failure domain)
- Multiple AZs in a region
- Multiple regions (with synchronous and asynchronous replication choices)
A YugabyteDB universe can consist of one or more keyspaces (a.k.a databases in other databases such as MySQL or Postgres). A keyspace is essentially a namespace and can contain one or more tables. Yugabyte automatically shards, replicates and load-balances these tables across the nodes in the universe, while respecting user-intent such as cross-AZ or region placement requirements, desired replication factor, and so on. Yugabyte automatically handles failures (e.g., node, process, AZ or region failures), and re-distributes and re-replicates data back to desired levels across the remaining available nodes while still respecting any data placement requirements.
A Yugabyte Universe can comprise of one or more clusters. Each cluster is a logical group of nodes running YB-TServers that are either performing strong (synchronous) replication of the user data or are in a timeline consistent (asynchronous) replication mode. The set of nodes that are performing strong replication are referred to as the Primary cluster and other groups are called Read Replica clusters. There is always one primary cluster in a universe and there can be zero or more read replica clusters in that universe. More information is here.
Note: In most of the docs, the term
universe are used interchangeably.
A YugabyteDB universe comprises of two sets of processes, YB-TServer and YB-Master. These serve different purposes.
The YB-TServer (aka the Yugabyte Tablet Server) processes are responsible for hosting/serving user data (e.g, tables).
The YB-Master (aka the Yugabyte Master Server) processes are responsible for keeping system metadata, coordinating system-wide operations such as create/alter drop tables, and initiating maintenance operations such as load-balancing.
YugabyteDB is architected to not have any single point of failure. The YB-TServer as well YB-Master processes use Raft, a distributed consensus algorithm, for replicating changes to user data or system metadata respectively across a set of nodes.
High Availability (HA) of the YB-Master’s functionalities and of the user-tables served by the YB-TServers is achieved by the failure-detection and new-leader election mechanisms that are built into the Raft implementation.
Below is an illustration of a simple 4-node Yugabyte universe:
The YB-TServer (short for Yugabyte Tablet Server) is the process that does the actual IO for end user requests. Recall from the previous section that data for a table is split/sharded into tablets. Each tablet is composed of one or more tablet-peers depending on the replication factor. And each YB-TServer hosts one or more tablet-peers.
Note: We will refer to the “tablet-peers hosted by a YB-TServer” simply as the “tablets hosted by a YB-TServer”.
Below is a pictorial illustration of this in the case of a 4 node Yugabyte universe, with one table that has 16 tablets and a replication factor of 3.
The tablet-peers corresponding to each tablet hosted on different YB-TServers form a Raft group and replicate data between each other. The system shown above comprises of 16 independent Raft groups. The details of this replication are covered in a previous section on replication.
Within each YB-TServer, there is a lot of cross-tablet intelligence built in to maximize resource efficiency. Below are just some of the ways the YB-TServer coordinates operations across tablets hosted by it:
Server-global block cache
The block cache is shared across the different tablets in a given YB-TServer. This leads to highly efficient memory utilization in cases when one tablet is read more often than others. For example, one table may have a read-heavy usage pattern compared to others. The block cache will automatically favor blocks of this table as the block cache is global across all tablet-peers.
The compactions are throttled across tablets in a given YB-TServer to prevent compaction storms. This prevents the often dreaded high foreground latencies during a compaction storm.
Small/Large Compaction Queues
Compactions are prioritized into large and small compactions with some prioritization to keep the system functional even in extreme IO patterns.
Server-global Memstore Limit
Tracks and enforces a global size across the memstores for different tablets. This makes sense when there is a skew in the write rate across tablets. For example, the scenario when there are tablets belonging to multiple tables in a single YB-TServer and one of the tables gets a lot more writes than the other tables. The write heavy table is allowed to grow much larger than it could if there was a per-tablet memory limit, allowing good write efficiency.
Auto-Sizing of Block Cache/Memstore
The block cache and memstores represent some of the larger memory-consuming components. Since these are global across all the tablet-peers, this makes memory management and sizing of these components across a variety of workloads very easy. In fact, based on the RAM available on the system, the YB-TServer automatically gives a certain percentage of the total available memory to the block cache, and another percentage to memstores.
Striping tablet load uniformly across data disks
On multi-SSD machines, the data (SSTable) and WAL (RAFT write-ahead-log) for various tablets of tables are evenly distributed across the attached disks on a per-table basis. This ensures that each disk handles an even amount of load for each table.
The YB-Master is the keeper of system meta-data/records, such as what tables exist in the system, where their tablets live, what users/roles exist, the permissions associated with them, and so on.
It is also responsible for coordinating background operations (such as load-balancing or initiating re-replication of under-replicated data) and performing a variety of administrative operations such as create/alter/drop of a table.
Note that the YB-Master is highly available as it forms a Raft group with its peers, and it is not in the critical path of IO against user tables.
Here are some of the functions of the YB-Master.
Coordination of Universe-wide Admin Operations
Examples of such operations are user-issued create/alter/drop table requests, as well as a creating a backup of a table. The YB-Master performs these operations with a guarantee that the operation is propagated to all tablets irrespective of the state of the YB-TServers hosting these tablets. This is essential because a YB-TServer failure while one of these universe-wide operations is in progress cannot affect the outcome of the operation by failing to apply it on some tablets.
Storage of System Metadata
The master stores system metadata such as the information about all the keyspaces, tables, roles, permissions, and assignment of tablets to YB-TServers. These system records are replicated across the YB-Masters for redundancy using Raft as well. The system metadata is also stored as a DocDB table by the YB-Master(s).
Authoritative Source of Tablet Assignments to YB-TServers
The YB-Master stores all tablets and the corresponding YB-TServers that currently host them. This map of tablets to the hosting YB-TServers is queried by clients (such as the YQL layer). Applications using the YB smart clients for various languages (such as Cassandra, Redis, or PostgreSQL(beta)) are very efficient in retrieving data. The smart clients query the YB-Master for the tablet to YB-TServer map and cache it. By doing so, the smart clients can talk directly to the correct YB-TServer to serve various queries without incurring additional network hops.
These operations performed throughout the lifetime of the universe in the background without impacting foreground read/write performance.
Data Placement & Load Balancing
The YB-Master leader does the initial placement (at CREATE table time) of tablets across YB-TServers to enforce any user-defined data placement constraints and ensure uniform load. In addition, during the lifetime of the universe, as nodes are added, fail or decommissioned, it continues to balance the load and enforce data placement constraints automatically.
Aside from ensuring that the number of tablets served by each YB-TServer is balanced across the universe, the YB-Masters also ensures that each node has a symmetric number of tablet-peer leaders across eligible nodes.
Re-replication of Data on Extended YB-TServer Failure
The YB-Master receives heartbeats from all the YB-TServers, and tracks their liveness. It detects if any YB-TServers has failed, and keeps track of the time interval for which the YB-TServer remains in a failed state. If the time duration of the failure extends beyond a threshold, it finds replacement YB-TServers to which the tablet data of the failed YB-TServer is re-replicated. Re-replication is initiated in a throttled fashion by the YB-Master leader so as to not impact the foreground operations of the universe.