@@ -167,7 +167,7 @@ A complete TDengine system runs on one or more physical nodes. Logically, it inc
**Management node (mnode)**: A virtual logical unit responsible for monitoring and maintaining the running status of all data nodes and load balancing among nodes (M in the figure). At the same time, the management node is also responsible for the storage and management of metadata (including users, databases, tables, static tags, etc.), so it is also called Meta Node. Multiple (up to 5) mnodes can be configured in a TDengine cluster, and they are automatically constructed into a virtual management node group (M0, M1, M2 in the figure). The master/slave mechanism is adopted for the mnode group and the data synchronization is carried out in a strongly consistent way. Any data update operation can only be executed on the master. The creation of mnode cluster is completed automatically by the system without manual intervention. There is at most one mnode on each dnode, which is uniquely identified by the EP of the data node to which it belongs. Each dnode automatically obtains the EP of the dnode where all mnodes in the whole cluster are located through internal messaging interaction.
**Virtual node group (VGroup)**: Vnodes on different data nodes can form a virtual node group to ensure the high availability of the system. The virtual node group is managed in a master/slave mechanism. Write operations can only be performed on the master vnode, and then replicated to slave vnodes, thus ensuring that one single replica of data is copied on multiple physical nodes. The number of virtual nodes in a vgroup equals the number of data replicas. If the number of replicas of a DB is N, the system must have at least N data nodes. The number of replicas can be specified by the parameter `replica` when creating DB, and the default is 1. Using the multi-replication feature of TDengine, the same high data reliability can be achieved without the need for expensive storage devices such as disk arrays. Virtual node group is created and managed by the management node, and the management node assigns a system unique ID, aka VGroup ID. If two virtual nodes have the same vnode group ID, means that they belong to the same group and the data is backed up to each other. The number of virtual nodes in a virtual node group can be dynamically changed, allowing only one, that is, no data replication. VGroup ID is never changed. Even if a virtual node group is deleted, its ID will not be reused.
**Virtual node group (VGroup)**: Vnodes on different data nodes can form a virtual node group to ensure the high availability of the system. The virtual node group is managed in a master/slave mechanism. Write operations can only be performed on the master vnode, and then replicated to slave vnodes, thus ensuring that one single replica of data is copied on multiple physical nodes. The number of virtual nodes in a vgroup equals the number of data replicas. If the number of replicas of a DB is N, the system must have at least N data nodes. The number of replicas can be specified by the parameter `“replica”` when creating DB, and the default is 1. Using the multi-replication feature of TDengine, the same high data reliability can be achieved without the need for expensive storage devices such as disk arrays. Virtual node group is created and managed by the management node, and the management node assigns a system unique ID, aka VGroup ID. If two virtual nodes have the same vnode group ID, means that they belong to the same group and the data is backed up to each other. The number of virtual nodes in a virtual node group can be dynamically changed, allowing only one, that is, no data replication. VGroup ID is never changed. Even if a virtual node group is deleted, its ID will not be reused.
**TAOSC**: TAOSC is the driver provided by TDengine to applications, which is responsible for dealing with the interaction between application and cluster, and provides the native interface of C/C++ language, which is embedded in JDBC, C #, Python, Go, Node.js language connection libraries. Applications interact with the whole cluster through TAOSC instead of directly connecting to data nodes in the cluster. This module is responsible for obtaining and caching metadata; forwarding requests for insertion, query, etc. to the correct data node; when returning the results to the application, TAOSC also needs to be responsible for the final level of aggregation, sorting, filtering and other operations. For JDBC, C/C++/C #/Python/Go/Node.js interfaces, this module runs on the physical node where the application is located. At the same time, in order to support the fully distributed RESTful interface, TAOSC has a running instance on each dnode of TDengine cluster.
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@@ -175,21 +175,21 @@ A complete TDengine system runs on one or more physical nodes. Logically, it inc
**Communication mode**: The communication among each data node of TDengine system, and among the application driver and each data node is carried out through TCP/UDP. Considering an IoT scenario, the data writing packets are generally not large, so TDengine uses UDP in addition to TCP for transmission, because UDP is more efficient and is not limited by the number of connections. TDengine implements its own timeout, retransmission, confirmation and other mechanisms to ensure reliable transmission of UDP. For packets with a data volume of less than 15K, UDP is adopted for transmission, and TCP is automatically adopted for transmission of packets with a data volume of more than 15K or query operations. At the same time, TDengine will automatically compress/decompress the data, digital sign/authenticate the data according to the configuration and data packet. For data replication among data nodes, only TCP is used for data transportation.
**FQDN configuration:** A data node has one or more FQDNs, which can be specified in the system configuration file taos.cfg with the parameter "fqdn". If it is not specified, the system will automatically use the hostname of the computer as its FQDN. If the node is not configured with FQDN, you can directly set the configuration parameter fqdn of the node to its IP address. However, IP is not recommended because IP address may be changed, and once it changes, the cluster will not work properly. The EP (End Point) of a data node consists of FQDN + Port. With FQDN, it is necessary to ensure the DNS service is running, or hosts files on nodes are configured properly.
**FQDN configuration:** A data node has one or more FQDNs, which can be specified in the system configuration file taos.cfg with the parameter “fqdn”. If it is not specified, the system will automatically use the hostname of the computer as its FQDN. If the node is not configured with FQDN, you can directly set the configuration parameter “fqdn” of the node to its IP address. However, IP is not recommended because IP address may be changed, and once it changes, the cluster will not work properly. The EP (End Point) of a data node consists of FQDN + Port. With FQDN, it is necessary to ensure the DNS service is running, or hosts files on nodes are configured properly.
**Port configuration**: The external port of a data node is determined by the system configuration parameter serverPort in TDengine, and the port for internal communication of cluster is serverPort+5. The data replication operation among data nodes in the cluster also occupies a TCP port, which is serverPort+10. In order to support multithreading and efficient processing of UDP data, each internal and external UDP connection needs to occupy 5 consecutive ports. Therefore, the total port range of a data node will be serverPort to serverPort + 10, for a total of 11 TCP/UDP ports. To run the system, make sure that the firewall keeps these ports open. Each data node can be configured with a different serverPort.
**Port configuration**: The external port of a data node is determined by the system configuration parameter “serverPort” in TDengine, and the port for internal communication of cluster is serverPort+5. The data replication operation among data nodes in the cluster also occupies a TCP port, which is serverPort+10. In order to support multithreading and efficient processing of UDP data, each internal and external UDP connection needs to occupy 5 consecutive ports. Therefore, the total port range of a data node will be serverPort to serverPort + 10, for a total of 11 TCP/UDP ports. To run the system, make sure that the firewall keeps these ports open. Each data node can be configured with a different serverPort.
**Cluster external connection**: TDengine cluster can accommodate one single, multiple or even thousands of data nodes. The application only needs to initiate a connection to any data node in the cluster. The network parameter required for connection is the End Point (FQDN plus configured port number) of a data node. When starting the application taos through CLI, the FQDN of the data node can be specified through the option `-h`, and the configured port number can be specified through `-p`. If the port is not configured, the system configuration parameter serverPort of TDengine will be adopted.
**Cluster external connection**: TDengine cluster can accommodate one single, multiple or even thousands of data nodes. The application only needs to initiate a connection to any data node in the cluster. The network parameter required for connection is the End Point (FQDN plus configured port number) of a data node. When starting the application taos through CLI, the FQDN of the data node can be specified through the option `-h`, and the configured port number can be specified through `-p`. If the port is not configured, the system configuration parameter “serverPort” of TDengine will be adopted.
**Inter-cluster communication**: Data nodes connect with each other through TCP/UDP. When a data node starts, it will obtain the EP information of the dnode where the mnode is located, and then establish a connection with the mnode in the system to exchange information. There are three steps to obtain EP information of the mnode:
1. Check whether the mnodeEpList file exists, if it does not exist or cannot be opened normally to obtain EP information of the mnode, skip to the second step;
2. Check the system configuration file taos.cfg to obtain node configuration parameters firstEp and secondEp (the node specified by these two parameters can be a normal node without mnode, in this case, the node will try to redirect to the mnode node when connected). If these two configuration parameters do not exist or do not exist in taos.cfg, or are invalid, skip to the third step;
2. Check the system configuration file taos.cfg to obtain node configuration parameters “firstEp” and “secondEp” (the node specified by these two parameters can be a normal node without mnode, in this case, the node will try to redirect to the mnode node when connected). If these two configuration parameters do not exist or do not exist in taos.cfg, or are invalid, skip to the third step;
3. Set your own EP as a mnode EP and run it independently. After obtaining the mnode EP list, the data node initiates the connection. It will successfully join the working cluster after connection. If not successful, it will try the next item in the mnode EP list. If all attempts are made, but the connection still fails, sleep for a few seconds before trying again.
**The choice of MNODE**: TDengine logically has a management node, but there is no separated execution code. The server-side only has a set of execution code taosd. So which data node will be the management node? This is determined automatically by the system without any manual intervention. The principle is as follows: when a data node starts, it will check its End Point and compare it with the obtained mnode EP List. If its EP exists in it, the data node shall start the mnode module and become a mnode. If your own EP is not in the mnode EP List, the mnode module will not start. During the system operation, due to load balancing, downtime and other reasons, mnode may migrate to the new dnode, while totally transparent without manual intervention. The modification of configuration parameters is the decision made by mnode itself according to resources usage.
**Add new data nodes:** After the system has a data node, it has become a working system. There are two steps to add a new node into the cluster. Step1: Connect to the existing working data node using TDengine CLI, and then add the End Point of the new data node with the command "create dnode"; Step 2: In the system configuration parameter file taos.cfg of the new data node, set the firstEp and secondEp parameters to the EP of any two data nodes in the existing cluster. Please refer to the detailed user tutorial for detailed steps. In this way, the cluster will be established step by step.
**Add new data nodes:** After the system has a data node, it has become a working system. There are two steps to add a new node into the cluster. Step1: Connect to the existing working data node using TDengine CLI, and then add the End Point of the new data node with the command "create dnode"; Step 2: In the system configuration parameter file taos.cfg of the new data node, set the “firstEp” and “secondEp” parameters to the EP of any two data nodes in the existing cluster. Please refer to the detailed user tutorial for detailed steps. In this way, the cluster will be established step by step.
**Redirection**: No matter about dnode or TAOSC, the connection to the mnode shall be initiated first, but the mnode is automatically created and maintained by the system, so the user does not know which dnode is running the mnode. TDengine only requires a connection to any working dnode in the system. Because any running dnode maintains the currently running mnode EP List, when receiving a connecting request from the newly started dnode or TAOSC, if it’s not a mnode by self, it will reply to the mnode EP List back. After receiving this list, TAOSC or the newly started dnode will try to establish the connection again. When the mnode EP List changes, each data node quickly obtains the latest list and notifies TAOSC through messaging interaction among nodes.
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@@ -221,7 +221,7 @@ Through TAOSC caching mechanism, mnode needs to be accessed only when a table is
The data stored by TDengine include collected time-series data, metadata related to database and tables, tag data, etc. These data are specifically divided into three parts:
- Time-series data: stored in vnode and composed of data, head and last files. The amount of data is large and query amount depends on the application scenario. Out-of-order writing is allowed, but delete operation is not supported for the time being, and update operation is only allowed when database update parameter is set to 1. By adopting the model with one table for each data collection point, the data of a given time period is continuously stored, and the writing against one single table is a simple appending operation. Multiple records can be read at one time, thus ensuring the insert and query operation of a single data collection point with the best performance.
- Time-series data: stored in vnode and composed of data, head and last files. The amount of data is large and query amount depends on the application scenario. Out-of-order writing is allowed, but delete operation is not supported for the time being, and update operation is only allowed when database “update” parameter is set to 1. By adopting the model with one table for each data collection point, the data of a given time period is continuously stored, and the writing against one single table is a simple appending operation. Multiple records can be read at one time, thus ensuring the insert and query operation of a single data collection point with the best performance.
- Tag data: meta files stored in vnode. Four standard operations of create, read, update and delete are supported. The amount of data is not large. If there are N tables, there are N records, so all can be stored in memory. To make tag filtering efficient, TDengine supports multi-core and multi-threaded concurrent queries. As long as the computing resources are sufficient, even in face of millions of tables, the tag filtering results will return in milliseconds.
- Metadata: stored in mnode, including system node, user, DB, Table Schema and other information. Four standard operations of create, delete, update and read are supported. The amount of these data are not large and can be stored in memory, moreover, the query amount is not large because of the client cache. Therefore, TDengine uses centralized storage management, however, there will be no performance bottleneck.
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@@ -244,7 +244,7 @@ The meta data of each table (including schema, tags, etc.) is also stored in vno
### Data Partitioning
In addition to vnode sharding, TDengine partitions the time-series data by time range. Each data file contains only one time range of time-series data, and the length of the time range is determined by DB's configuration parameter `days`. This method of partitioning by time rang is also convenient to efficiently implement the data retention policy. As long as the data file exceeds the specified number of days (system configuration parameter `keep`), it will be automatically deleted. Moreover, different time ranges can be stored in different paths and storage media, so as to facilitate the tiered-storage. Cold/hot data can be stored in different storage meida to reduce the storage cost.
In addition to vnode sharding, TDengine partitions the time-series data by time range. Each data file contains only one time range of time-series data, and the length of the time range is determined by DB's configuration parameter `“days”`. This method of partitioning by time rang is also convenient to efficiently implement the data retention policy. As long as the data file exceeds the specified number of days (system configuration parameter `“keep”`), it will be automatically deleted. Moreover, different time ranges can be stored in different paths and storage media, so as to facilitate the tiered-storage. Cold/hot data can be stored in different storage meida to reduce the storage cost.
In general, **TDengine splits big data by vnode and time range in two dimensions** to manage the data efficiently with horizontal scalability.
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@@ -252,7 +252,7 @@ In general, **TDengine splits big data by vnode and time range in two dimensions
Each dnode regularly reports its status (including hard disk space, memory size, CPU, network, number of virtual nodes, etc.) to the mnode (virtual management node), so mnode knows the status of the entire cluster. Based on the overall status, when the mnode finds a dnode is overloaded, it will migrate one or more vnodes to other dnodes. During the process, TDengine services keep running and the data insertion, query and computing operations are not affected.
If the mnode has not received the dnode status for a period of time, the dnode will be treated as offline. When offline lasts a certain period of time (configured by parameter `offlineThreshold`), the dnode will be forcibly removed from the cluster by mnode. If the number of replicas of vnodes on this dnode is greater than one, the system will automatically create new replicas on other dnodes to ensure the replica number. If there are other mnodes on this dnode and the number of mnodes replicas is greater than one, the system will automatically create new mnodes on other dnodes to ensure the replica number.
If the mnode has not received the dnode status for a period of time, the dnode will be treated as offline. When offline lasts a certain period of time (configured by parameter `“offlineThreshold”`), the dnode will be forcibly removed from the cluster by mnode. If the number of replicas of vnodes on this dnode is greater than one, the system will automatically create new replicas on other dnodes to ensure the replica number. If there are other mnodes on this dnode and the number of mnodes replicas is greater than one, the system will automatically create new mnodes on other dnodes to ensure the replica number.
When new data nodes are added to the cluster, with new computing and storage resources are added, the system will automatically start the load balancing process.
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@@ -270,7 +270,7 @@ Master Vnode uses a writing process as follows:
<center> Figure 3: TDengine Master writing process </center>
1. Master vnode receives the application data insertion request, verifies, and moves to next step;
2. If the system configuration parameter `walLevel` is greater than 0, vnode will write the original request packet into database log file WAL. If walLevel is set to 2 and fsync is set to 0, TDengine will make WAL data written immediately to ensure that even system goes down, all data can be recovered from database log file;
2. If the system configuration parameter `“walLevel”` is greater than 0, vnode will write the original request packet into database log file WAL. If walLevel is set to 2 and fsync is set to 0, TDengine will make WAL data written immediately to ensure that even system goes down, all data can be recovered from database log file;
3. If there are multiple replicas, vnode will forward data packet to slave vnodes in the same virtual node group, and the forwarded packet has a version number with data;
4. Write into memory and add the record to “skip list”;
5. Master vnode returns a confirmation message to the application, indicating a successful writing.
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@@ -284,7 +284,7 @@ For a slave vnode, the write process as follows:
<center> Figure 4: TDengine Slave Writing Process </center>
1. Slave vnode receives a data insertion request forwarded by Master vnode;
2. If the system configuration parameter `walLevel` is greater than 0, vnode will write the original request packet into database log file WAL. If walLevel is set to 2 and fsync is set to 0, TDengine will make WAL data written immediately to ensure that even system goes down, all data can be recovered from database log file;
2. If the system configuration parameter `“walLevel”` is greater than 0, vnode will write the original request packet into database log file WAL. If walLevel is set to 2 and fsync is set to 0, TDengine will make WAL data written immediately to ensure that even system goes down, all data can be recovered from database log file;
3. Write into memory and add the record to “skip list”.
Compared with Master vnode, slave vnode has no forwarding or reply confirmation step, means two steps less. But writing into memory and WAL is exactly the same.
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@@ -338,17 +338,17 @@ Each vnode has its own independent memory, and it is composed of multiple memory
TDengine uses a data-driven method to write the data from buffer into hard disk for persistent storage. When the cached data in vnode reaches a certain volume, TDengine will also pull up the disk-writing thread to write the cached data into persistent storage in order not to block subsequent data writing. TDengine will open a new database log file when the data is written, and delete the old database log file after written successfully to avoid unlimited log growth.
To make full use of the characteristics of time-series data, TDengine splits the data stored in persistent storage by a vnode into multiple files, each file only saves data for a fixed number of days, which is determined by the system configuration parameter `days`. By so, for the given start and end date of a query, you can locate the data files to open immediately without any index, thus greatly speeding up reading operations.
To make full use of the characteristics of time-series data, TDengine splits the data stored in persistent storage by a vnode into multiple files, each file only saves data for a fixed number of days, which is determined by the system configuration parameter `“days”`. By so, for the given start and end date of a query, you can locate the data files to open immediately without any index, thus greatly speeding up reading operations.
For time-series data, there is generally a retention policy, which is determined by the system configuration parameter `keep`. Data files exceeding this set number of days will be automatically deleted by the system to free up storage space.
For time-series data, there is generally a retention policy, which is determined by the system configuration parameter `“keep”`. Data files exceeding this set number of days will be automatically deleted by the system to free up storage space.
Given “days” and “keep” parameters, the total number of data files in a vnode is: keep/days. The total number of data files should not be too large or too small. 10 to 100 is appropriate. Based on this principle, reasonable days can be set. In the current version, parameter “keep” can be modified, but parameter “days” cannot be modified once it is set.
In each data file, the data of a table is stored by blocks. A table can have one or more data file blocks. In a file block, data is stored in columns, occupying a continuous storage space, thus greatly improving the reading speed. The size of file block is determined by the system parameter `maxRows` (the maximum number of records per block), and the default value is 4096. This value should not be too large or too small. If it is too large, the data locating in search will cost longer; if too small, the index of data block is too large, and the compression efficiency will be low with slower reading speed.
In each data file, the data of a table is stored by blocks. A table can have one or more data file blocks. In a file block, data is stored in columns, occupying a continuous storage space, thus greatly improving the reading speed. The size of file block is determined by the system parameter `“maxRows”` (the maximum number of records per block), and the default value is 4096. This value should not be too large or too small. If it is too large, the data locating in search will cost longer; if too small, the index of data block is too large, and the compression efficiency will be low with slower reading speed.
Each data file (with a .data postfix) has a corresponding index file (with a .head postfix). The index file has summary information of a data block for each table, recording the offset of each data block in the data file, start and end time of data and other information, so as to lead system quickly locate the data to be found. Each data file also has a corresponding last file (with a .last postfix), which is designed to prevent data block fragmentation when written in disk. If the number of written records from a table does not reach the system configuration parameter `minRows` (minimum number of records per block), it will be stored in the last file first. When write to disk next time, the newly written records will be merged with the records in last file and then written into data file.
Each data file (with a .data postfix) has a corresponding index file (with a .head postfix). The index file has summary information of a data block for each table, recording the offset of each data block in the data file, start and end time of data and other information, so as to lead system quickly locate the data to be found. Each data file also has a corresponding last file (with a .last postfix), which is designed to prevent data block fragmentation when written in disk. If the number of written records from a table does not reach the system configuration parameter `“minRows”` (minimum number of records per block), it will be stored in the last file first. When write to disk next time, the newly written records will be merged with the records in last file and then written into data file.
When data is written to disk, it is decided whether to compress the data according to system configuration parameter `comp`. TDengine provides three compression options: no compression, one-stage compression and two-stage compression, corresponding to comp values of 0, 1 and 2 respectively. One-stage compression is carried out according to the type of data. Compression algorithms include delta-delta coding, simple 8B method, zig-zag coding, LZ4 and other algorithms. Two-stage compression is based on one-stage compression and compressed by general compression algorithm, which has higher compression ratio.
When data is written to disk, it is decided whether to compress the data according to system configuration parameter `“comp”`. TDengine provides three compression options: no compression, one-stage compression and two-stage compression, corresponding to comp values of 0, 1 and 2 respectively. One-stage compression is carried out according to the type of data. Compression algorithms include delta-delta coding, simple 8B method, zig-zag coding, LZ4 and other algorithms. Two-stage compression is based on one-stage compression and compressed by general compression algorithm, which has higher compression ratio.
