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Graph blockchain
Publish: 2021-04-30 12:59:17
1.
blockchain is a new application mode of distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and other computer technologies. Blockchain is an important concept of bitcoin,
in essence, it is a decentralized database. At the same time, as the underlying technology of bitcoin, it is a series of data blocks generated by using cryptographic methods. Each data block contains a batch of information of bitcoin network transactions, Used to verify the validity of its information (anti-counterfeiting) and generate the next block
extended data
most blockchain public chains are limited by scalability. The biggest feature of blockchain technology is decentralization, which requires that all accounts in the network need to deal with the accounting process. Distributed accounting has high security, low misoperation rate, political neutrality and correctness
however, blockchain technology embraces these features at the same time, sacrificing scalability, unable to meet the personalized supervision, and slightly insufficient in protecting data privacy. Moreover, with the increase of the number of ledger, the interaction delay will increase exponentially, that is to say, the more ledger in the blockchain network, the higher the delay
2. In order to make cybervein more international, two brand upgrades were carried out: for the first time, cybervein was defined as connecting the data that runs the world. At the same time, the logo was changed to purple, becoming a bright flag in the big wave of blockchain; For the second time, the brand slogan was changed to "from then on, data becomes valuable", and the resounding international slogan of decentralized power for data was called out!
3. Mining boy seems to be, you have a try!!!
4. DAG (directed acyclic graph) is a common data structure in the computer field. Because of some characteristics brought by the unique topology structure, it is often used to deal with dynamic planning, search for the shortest path in navigation, data compression and other scenes. Since 15 years ago, the concept of blockchain has been singled out. Before that, blockchain was just a data structure in bitcoin technology, and when block and chain were connected in Nakamoto's white paper, it was just a chain of blocks. With the emergence of the concept of Ethereum decentralized computer, many people began to call Ethereum blockchain 2.0, while bitcoin was classified as blockchain 1.0. As for blockchain 3.0, in order to seize the naming right of blockchain 3.0, it may be DAG.
5. We say that the blockchain is not mature at present, and there are various problems, such as slow processing speed, high handling charges, security risks and so on. These are the most intuitive experience of users, and the experience is not very good. Another problem of blockchain is high concurrency
let's talk about the problem of high concurrency. High concurrency is a problem in the computer field. In short, the problem of high concurrency is that the system cannot run multiple tasks at the same time smoothly
many tasks are running at the same time, and a large number of users rush in. The system can't bear so many tasks. There will be high concurrency problems, and your system will be stuck, just like the 12306 system is always stuck ring the Spring Festival, which may be caused by the high concurrency problems
the traditional Internet still has the problem of high concurrency, which naturally exists in the blockchain network. After all, the maturity of the blockchain is still far behind that of the traditional Internet. However, if there is no safe, reliable and efficient public chain, the development of the whole blockchain instry will be seriously restricted, and the application landing is empty talk
in this context, DAG technology has been proposed, DAG's full name is "directed acyclic graph", which is translated into "directed acyclic graph" in Chinese
What's the matter with DAG directed acyclic graph and what role it can play? Let's explain< Dag: a new data structure
DAG, Chinese name is "directed acyclic graph", literally, "directed & quot; That is to say, it has direction,
"no loop" means that it has no loop and cannot form a closed loop. Therefore, DAG is actually a new type of data structure. This data structure has direction and can not form a closed loop
in terms of traditional blocks, we always take "block" as the unit, and a block often contains multiple transaction information. In DAG, there is no concept of block. Instead, it takes "unit" as the unit. Each unit records the transaction of a single user. The unit is not a block, but a transaction. In this way, the time of packing blocks can be saved
in short, the biggest difference between blockchain and DAG directed acyclic graph is that blockchain is one block after another to store and verify the distributed ledger of transactions, while DAG regards each transaction as a block, and each transaction can be linked to multiple previous transactions for verification< Second, the working principle of DAG
in the traditional blockchain, take bitcoin as an example, it is a single chain structure. The blocks are arranged according to the time stamp sequence (as shown in Figure 1), and the data is recorded on a main chain. To use an inappropriate metaphor, this "single chain" structure is a chain arranged word by word
there is only one single chain in the blockchain, so it can not be executed concurrently when the block is packaged. The new block will be added to the original longest chain, and all nodes will follow the longest chain and continue to spread infinitely in the order of timestamp. For DAG, each newly added unit is not only added to one unit of the longest chain, but also to all previous units (as shown in Figure 2)
for example: suppose I publish a new transaction, and there are two effective transaction units in DAG structure, then my transaction unit will actively link to the previous two at the same time to verify and confirm until it is linked to Genesis unit, and the hash of the previous unit will be included in its own unit
in other words, if you want to make a transaction, you have to verify the previous transaction, specifically several transactions, according to different rules. This verification method enables DAG to write many transactions asynchronously and concurrently, and finally forms a topological tree structure, which greatly improves the scalability
according to DAG directed acyclic graph, every transaction is directly involved in the maintenance of the whole network. When the transaction is initiated, the whole network is broadcast directly, skipping the block packing stage. In this way, the time of block packing is saved, and the transaction processing efficiency of the blockchain is improved
with the increase of time, the blockchains of all transactions are interconnected to form a graph structure. If you want to change the data, it is not just the problem of several blocks, but the data change of the whole block diagram. Dag is more complex and difficult to change
to sum up, DAG, as a new type of decentralized data structure, belongs to a kind of generalized blockchain and has the attribute of decentralization. However, the differences between the two are as follows:
the composition unit of blockchain is block and the composition unit of DAG is TX
blockchain is single threaded, DAG is multi-threaded
all transactions of blockchain are recorded in the same block, and each transaction of DAG is recorded in each transaction separately
blockchain needs miners, DAG doesn't need miners< (3) representative of DAG: iota is undoubtedly the most famous representative project of DAG. It can be said that it is precisely because iota, the currency, broke into the fourth place in market value in the second half of 2017 that people really realized its underlying technology: DAG directed acyclic graph
iota puts forward the concept of "entanglement" on the basis of DAG directed acyclic graph. In iota, there is no concept of block, and the minimum unit of consensus is transaction. Each transaction will refer to the past two transaction records hash, so that the previous transaction will prove the legitimacy of the past two transactions and indirectly prove the legitimacy of all previous transactions. In this way, a small number of nodes such as miners in the traditional blockchain are no longer needed to verify transactions and package blocks, so as to improve efficiency and save transaction costs< Fourth, the current situation of DAG
although DAG directed acyclic graph can make up for some disadvantages of traditional blockchain in theory, it is not mature at present, and it has been applied to the field of digital currency for a short time
it did not take as long as 10 years to verify the security of the whole system as bitcoin did, nor did it achieve a wide range of application scenarios as Ethereum did. However, some voices now propose to adopt the data structure of "traditional blockchain + DAG", but there is no outstanding case, so I won't say more here
to sum up, in this section, we introce the derivative technology of blockchain: DAG directed acyclic graph, which is a new data structure, and can significantly improve the efficiency and power of blockchain transaction processing.
let's talk about the problem of high concurrency. High concurrency is a problem in the computer field. In short, the problem of high concurrency is that the system cannot run multiple tasks at the same time smoothly
many tasks are running at the same time, and a large number of users rush in. The system can't bear so many tasks. There will be high concurrency problems, and your system will be stuck, just like the 12306 system is always stuck ring the Spring Festival, which may be caused by the high concurrency problems
the traditional Internet still has the problem of high concurrency, which naturally exists in the blockchain network. After all, the maturity of the blockchain is still far behind that of the traditional Internet. However, if there is no safe, reliable and efficient public chain, the development of the whole blockchain instry will be seriously restricted, and the application landing is empty talk
in this context, DAG technology has been proposed, DAG's full name is "directed acyclic graph", which is translated into "directed acyclic graph" in Chinese
What's the matter with DAG directed acyclic graph and what role it can play? Let's explain< Dag: a new data structure
DAG, Chinese name is "directed acyclic graph", literally, "directed & quot; That is to say, it has direction,
"no loop" means that it has no loop and cannot form a closed loop. Therefore, DAG is actually a new type of data structure. This data structure has direction and can not form a closed loop
in terms of traditional blocks, we always take "block" as the unit, and a block often contains multiple transaction information. In DAG, there is no concept of block. Instead, it takes "unit" as the unit. Each unit records the transaction of a single user. The unit is not a block, but a transaction. In this way, the time of packing blocks can be saved
in short, the biggest difference between blockchain and DAG directed acyclic graph is that blockchain is one block after another to store and verify the distributed ledger of transactions, while DAG regards each transaction as a block, and each transaction can be linked to multiple previous transactions for verification< Second, the working principle of DAG
in the traditional blockchain, take bitcoin as an example, it is a single chain structure. The blocks are arranged according to the time stamp sequence (as shown in Figure 1), and the data is recorded on a main chain. To use an inappropriate metaphor, this "single chain" structure is a chain arranged word by word
there is only one single chain in the blockchain, so it can not be executed concurrently when the block is packaged. The new block will be added to the original longest chain, and all nodes will follow the longest chain and continue to spread infinitely in the order of timestamp. For DAG, each newly added unit is not only added to one unit of the longest chain, but also to all previous units (as shown in Figure 2)
for example: suppose I publish a new transaction, and there are two effective transaction units in DAG structure, then my transaction unit will actively link to the previous two at the same time to verify and confirm until it is linked to Genesis unit, and the hash of the previous unit will be included in its own unit
in other words, if you want to make a transaction, you have to verify the previous transaction, specifically several transactions, according to different rules. This verification method enables DAG to write many transactions asynchronously and concurrently, and finally forms a topological tree structure, which greatly improves the scalability
according to DAG directed acyclic graph, every transaction is directly involved in the maintenance of the whole network. When the transaction is initiated, the whole network is broadcast directly, skipping the block packing stage. In this way, the time of block packing is saved, and the transaction processing efficiency of the blockchain is improved
with the increase of time, the blockchains of all transactions are interconnected to form a graph structure. If you want to change the data, it is not just the problem of several blocks, but the data change of the whole block diagram. Dag is more complex and difficult to change
to sum up, DAG, as a new type of decentralized data structure, belongs to a kind of generalized blockchain and has the attribute of decentralization. However, the differences between the two are as follows:
the composition unit of blockchain is block and the composition unit of DAG is TX
blockchain is single threaded, DAG is multi-threaded
all transactions of blockchain are recorded in the same block, and each transaction of DAG is recorded in each transaction separately
blockchain needs miners, DAG doesn't need miners< (3) representative of DAG: iota is undoubtedly the most famous representative project of DAG. It can be said that it is precisely because iota, the currency, broke into the fourth place in market value in the second half of 2017 that people really realized its underlying technology: DAG directed acyclic graph
iota puts forward the concept of "entanglement" on the basis of DAG directed acyclic graph. In iota, there is no concept of block, and the minimum unit of consensus is transaction. Each transaction will refer to the past two transaction records hash, so that the previous transaction will prove the legitimacy of the past two transactions and indirectly prove the legitimacy of all previous transactions. In this way, a small number of nodes such as miners in the traditional blockchain are no longer needed to verify transactions and package blocks, so as to improve efficiency and save transaction costs< Fourth, the current situation of DAG
although DAG directed acyclic graph can make up for some disadvantages of traditional blockchain in theory, it is not mature at present, and it has been applied to the field of digital currency for a short time
it did not take as long as 10 years to verify the security of the whole system as bitcoin did, nor did it achieve a wide range of application scenarios as Ethereum did. However, some voices now propose to adopt the data structure of "traditional blockchain + DAG", but there is no outstanding case, so I won't say more here
to sum up, in this section, we introce the derivative technology of blockchain: DAG directed acyclic graph, which is a new data structure, and can significantly improve the efficiency and power of blockchain transaction processing.
6. DAG, Chinese name & quot; Directed acyclic graph & quot& quot; Directed & quot; It means that there is a direction. To be exact, it should be in the same direction; Acyclic & quot; It means that there is no closed loop. In DAG, there is no concept of block. Its constituent units are transactions, and each unit records the transactions of a single user, which saves the time of packing blocks. In other words, if you want to carry out a transaction, you must verify the previous transaction, and verify several transactions according to different rules. With this verification method, DAG can write many transactions asynchronously and concurrently, and finally form a topological tree structure, which can greatly improve the scalability.
7. In the cloud technology stack, one of the best software capabilities is the PAAS platform and services. In the list of China's top 100 software enterprises in 2018, Huawei has won the first place for 16 consecutive years. Huawei cloud is based on the accumulation of 30 years of experience in Huawei's software capabilities. Since 2016, Huawei cloud enterprise application services have launched PAAS procts one after another
ring the Huawei analyst conference (has2019) in 2019, Dr. Xiong Ying, chief scientist of Huawei cloud PAAS and chief designer of Huawei cloud intelligent application platform, made an appearance to introce the whole stack of PAAS technology formed by Huawei cloud in the past few years and the complete cloud native computing platform Huawei cloud intelligent application platform 3.0. As a founding member director of CNCF (cloud native Computing Foundation), Xiong Ying, with more than 20 years of experience in software development and architecture design, has profound theoretical and practical experience in the field of cloud native computing. Xiong Ying said that in view of the significant impact of cloud native on the future enterprise software instry, Huawei cloud included it in the scope of strategic technology investment in 2015, and now has made a lot of achievements and become the leader of cloud native technology<
(Dr. Xiong Ying, chief scientist of Huawei cloud PAAS and chief designer of Huawei cloud intelligent application platform)
the advantage of Huawei cloud enterprise application service technology represented by Huawei cloud intelligent application platform 3.0 lies in the capability of full stack cloud native computing and the support platform for digital transformation, with the goal of making it easier for enterprises to go to the cloud Digital transformation is more intelligent. In the field of cloud native computing, the biggest difficulty in the promotion of kubernetes and cloud native technology lies in the technical complexity. Huawei cloud has launched simple and easy-to-use procts and services in the "troika" field of cloud native technology, such as kubernetes + docker, micro services and serverless, continuously lowering the threshold of cloud native technology
Huawei cloud intelligent application platform 3.0 integrates Huawei's software technology capabilities, condenses Huawei's practice of global digital transformation and Huawei's continuous investment achievements in open source software over the years. It can be called "the top 100 software companies" of Huawei and a masterpiece of the cloud era<
panorama of Huawei's cloud enterprise application services
the overall architecture of Huawei's cloud enterprise application services not only absorbs the world's top cloud native series of open source projects, but also integrates Huawei's own characteristic technology system. The main features of Huawei cloud intelligent application platform 3.0 include one "base", two application innovation platforms and one application innovation solution: one "base" is servicestage micro service application platform, and two application innovation platforms are enterprise integration platform Roma, intelligent edge platform IEF, and blockchain solution BCS. Huawei cloud container multi cloud and hybrid cloud management platform (MCP), the first in the whole instry, is the carrier of Huawei cloud intelligent application platform 3.0, which was released one month earlier than Google's anthos
as for the whole stack technology of Huawei cloud enterprise application services, it includes: one stop micro service application management platform, including servicestage micro service cloud application platform, application choreography service AOS, micro service engine CSE, container image service SWR, Application Performance Management APM, cloud performance testing service CPTs, application operation and maintenance management AOM; Enterprise Cloud middleware, including redis, DMS, apig and BCS; Kubernetes container platform, including cloud container engine CCE and cloud container instance CCI; High performance serverless server less function functiongraph; And intelligent edge cloud IEF and enterprise integration platform Roma
specifically, Huawei cloud enterprise application service takes kubernetes and other container technologies as the core, and provides cloud container engine CCE and cloud container instance CCI around the core functions of kubernetes. Since the launch of CCE in 2016, Huawei has become the first batch of global kubernetes certified service providers in 2017, and CCE has also passed the consistency certification of kubernetes in the first batch. CCE is a high-performance, highly reliable public cloud container full stack solution developed by Huawei cloud. It runs through the application development, delivery and operation and maintenance process, provides a complete one-stop cloud application lifecycle management solution, and deeply integrates the computing, storage and network capabilities of Huawei cloud
in terms of micro service governance at the bottom of the container, servicestage is a cloud native application development platform that condenses Huawei's Micro service team's years of research and development experience. It provides enterprises with full stack solutions for AI, blockchain, micro service, mobile and web application development, helping users quickly create enterprise level cloud native applications and accelerating business innovation. Servicestage provides spring cloud, service mesh and servicecomb Commercial Version (CSE) to help enterprises quickly build distributed applications based on microservice architecture
servicestage can support multiple programming languages, integrate eclipse, idea, Jenkins, Maven and other tool ecology, support seamless integration of offline development environment and online cloud environment, and provide full stack and life cycle capabilities such as application development, compilation, construction, release, deployment, configuration, pressure testing, online, operation and maintenance and governance for Devops. The micro service engine CSE is a one-stop micro service management platform, which provides a high-performance micro service framework and one-stop service registration, service governance, dynamic configuration and distributed transaction management console to help users realize the rapid development and high availability operation and maintenance of micro service applications
in terms of serverless function computing, Huawei has launched function services in 2017, and is the first cloud service provider in China to publish function choreography services. Huawei cloud launched the world's first server free container instance CCI based on kubernetes. Users only need to manage the container business running on kubernetes, and the rest of the underlying computing resources are managed by Huawei cloud automation
in addition to the "troika" of cloud native computing, the enterprise integration platform Roma and intelligent edge platform IEF of Huawei's cloud enterprise application service meet the needs of large multinational enterprises' complex computing environment connection and the collaboration between cloud and edge computing. Roma can connect enterprise IT systems, data, messages, APIs, devices, cloud services, and provide a unified application and data integration platform. Rama comes from Huawei's internal information construction and integration experience, which helps enterprises simplify integration and accelerate application to the cloud. In the scenarios of on cloud and off cloud application integration, inter cloud application integration, cross regional integration, device data integration, enterprise capacity opening, B2B integration, business to sea integration and so on, Roma solves the problems of connecting traditional applications and cloud native applications, instrial and it equipment and data, private cloud and public cloud in the process of enterprise digital transformation Global nodes and other complex integration and connection requirements. Intelligent edge platform IEF extends Huawei's cloud AI service to the edge side, intelligentizes the edge nodes, fully meets the real-time requirements of business, and optimizes the use of computing resources
the world's first container multi cloud & hybrid cloud solution (MCP) of Huawei cloud provides the ability of unified monitoring, deployment, operation and maintenance of kubernetes clusters and cloud native applications across cloud platforms (between different public clouds or from public cloud to private cloud), as well as the cross cloud unified governance and regional affinity strategy of business traffic, Help enterprise customers easily cope with the impact of business traffic peak, cloud single point of downtime and the demands of business global integration and regional access.
ring the Huawei analyst conference (has2019) in 2019, Dr. Xiong Ying, chief scientist of Huawei cloud PAAS and chief designer of Huawei cloud intelligent application platform, made an appearance to introce the whole stack of PAAS technology formed by Huawei cloud in the past few years and the complete cloud native computing platform Huawei cloud intelligent application platform 3.0. As a founding member director of CNCF (cloud native Computing Foundation), Xiong Ying, with more than 20 years of experience in software development and architecture design, has profound theoretical and practical experience in the field of cloud native computing. Xiong Ying said that in view of the significant impact of cloud native on the future enterprise software instry, Huawei cloud included it in the scope of strategic technology investment in 2015, and now has made a lot of achievements and become the leader of cloud native technology<
(Dr. Xiong Ying, chief scientist of Huawei cloud PAAS and chief designer of Huawei cloud intelligent application platform)
the advantage of Huawei cloud enterprise application service technology represented by Huawei cloud intelligent application platform 3.0 lies in the capability of full stack cloud native computing and the support platform for digital transformation, with the goal of making it easier for enterprises to go to the cloud Digital transformation is more intelligent. In the field of cloud native computing, the biggest difficulty in the promotion of kubernetes and cloud native technology lies in the technical complexity. Huawei cloud has launched simple and easy-to-use procts and services in the "troika" field of cloud native technology, such as kubernetes + docker, micro services and serverless, continuously lowering the threshold of cloud native technology
Huawei cloud intelligent application platform 3.0 integrates Huawei's software technology capabilities, condenses Huawei's practice of global digital transformation and Huawei's continuous investment achievements in open source software over the years. It can be called "the top 100 software companies" of Huawei and a masterpiece of the cloud era<
panorama of Huawei's cloud enterprise application services
the overall architecture of Huawei's cloud enterprise application services not only absorbs the world's top cloud native series of open source projects, but also integrates Huawei's own characteristic technology system. The main features of Huawei cloud intelligent application platform 3.0 include one "base", two application innovation platforms and one application innovation solution: one "base" is servicestage micro service application platform, and two application innovation platforms are enterprise integration platform Roma, intelligent edge platform IEF, and blockchain solution BCS. Huawei cloud container multi cloud and hybrid cloud management platform (MCP), the first in the whole instry, is the carrier of Huawei cloud intelligent application platform 3.0, which was released one month earlier than Google's anthos
as for the whole stack technology of Huawei cloud enterprise application services, it includes: one stop micro service application management platform, including servicestage micro service cloud application platform, application choreography service AOS, micro service engine CSE, container image service SWR, Application Performance Management APM, cloud performance testing service CPTs, application operation and maintenance management AOM; Enterprise Cloud middleware, including redis, DMS, apig and BCS; Kubernetes container platform, including cloud container engine CCE and cloud container instance CCI; High performance serverless server less function functiongraph; And intelligent edge cloud IEF and enterprise integration platform Roma
specifically, Huawei cloud enterprise application service takes kubernetes and other container technologies as the core, and provides cloud container engine CCE and cloud container instance CCI around the core functions of kubernetes. Since the launch of CCE in 2016, Huawei has become the first batch of global kubernetes certified service providers in 2017, and CCE has also passed the consistency certification of kubernetes in the first batch. CCE is a high-performance, highly reliable public cloud container full stack solution developed by Huawei cloud. It runs through the application development, delivery and operation and maintenance process, provides a complete one-stop cloud application lifecycle management solution, and deeply integrates the computing, storage and network capabilities of Huawei cloud
in terms of micro service governance at the bottom of the container, servicestage is a cloud native application development platform that condenses Huawei's Micro service team's years of research and development experience. It provides enterprises with full stack solutions for AI, blockchain, micro service, mobile and web application development, helping users quickly create enterprise level cloud native applications and accelerating business innovation. Servicestage provides spring cloud, service mesh and servicecomb Commercial Version (CSE) to help enterprises quickly build distributed applications based on microservice architecture
servicestage can support multiple programming languages, integrate eclipse, idea, Jenkins, Maven and other tool ecology, support seamless integration of offline development environment and online cloud environment, and provide full stack and life cycle capabilities such as application development, compilation, construction, release, deployment, configuration, pressure testing, online, operation and maintenance and governance for Devops. The micro service engine CSE is a one-stop micro service management platform, which provides a high-performance micro service framework and one-stop service registration, service governance, dynamic configuration and distributed transaction management console to help users realize the rapid development and high availability operation and maintenance of micro service applications
in terms of serverless function computing, Huawei has launched function services in 2017, and is the first cloud service provider in China to publish function choreography services. Huawei cloud launched the world's first server free container instance CCI based on kubernetes. Users only need to manage the container business running on kubernetes, and the rest of the underlying computing resources are managed by Huawei cloud automation
in addition to the "troika" of cloud native computing, the enterprise integration platform Roma and intelligent edge platform IEF of Huawei's cloud enterprise application service meet the needs of large multinational enterprises' complex computing environment connection and the collaboration between cloud and edge computing. Roma can connect enterprise IT systems, data, messages, APIs, devices, cloud services, and provide a unified application and data integration platform. Rama comes from Huawei's internal information construction and integration experience, which helps enterprises simplify integration and accelerate application to the cloud. In the scenarios of on cloud and off cloud application integration, inter cloud application integration, cross regional integration, device data integration, enterprise capacity opening, B2B integration, business to sea integration and so on, Roma solves the problems of connecting traditional applications and cloud native applications, instrial and it equipment and data, private cloud and public cloud in the process of enterprise digital transformation Global nodes and other complex integration and connection requirements. Intelligent edge platform IEF extends Huawei's cloud AI service to the edge side, intelligentizes the edge nodes, fully meets the real-time requirements of business, and optimizes the use of computing resources
the world's first container multi cloud & hybrid cloud solution (MCP) of Huawei cloud provides the ability of unified monitoring, deployment, operation and maintenance of kubernetes clusters and cloud native applications across cloud platforms (between different public clouds or from public cloud to private cloud), as well as the cross cloud unified governance and regional affinity strategy of business traffic, Help enterprise customers easily cope with the impact of business traffic peak, cloud single point of downtime and the demands of business global integration and regional access.
8. Generally speaking, in the first tier cities, bat's starting salary for fresh graates is not high, but as long as they work hard and have outstanding ability, in fact, it's very easy to get an annual salary of more than 150000 yuan in the two or three years after they are employed. In third tier Internet companies, under the same conditions, the annual salary of ordinary technical staff can generally reach about 150000 yuan. The salary of ordinary employees in quasi second tier Internet companies can reach or exceed 200000 yuan, which is absolutely enviable compared with many traditional instries. After more than five years of work experience, the income gap in Internet enterprises will widen
such an attractive salary is definitely what everyone wants to join. However, the condition for joining is to master certain skills. Based on the requirements of many big data companies, the statistics are as follows:
1
2. Skillfully use Hadoop, M / R, hive, storm and other development tools
3. Familiar with Linux commands and shell programming
4. Sensitive to data, good logical analysis ability, good communication skills and team spirit
5. Familiar with impala, Druid, mdrill, elasticsearch and other big data tools is preferred
according to the requirements of enterprises for big data engineers, the technologies you need to learn are as follows:
stage 1, big data foundation - Java language foundation
(1) Java language foundation
(2) HTML, CSS and JavaScript
(3) JavaWeb and database
stage 2, Linux & Hadoop ecosystem
linux system, Hadoop offline computing outline Distributed database HBase, data warehouse hive, data migration tool sqoop, flume distributed log framework
stage 3, distributed computing framework and spark & strom ecosystem
(1) distributed computing framework
python programming language, Scala programming language, spark big data processing, spark streaming big data processing, spark mlib machine learning, etc Calculation of spark graphx diagram, actual combat 1: recommendation system based on Spark (real project of a front-line company), actual combat 2: sina.com www.sina.com.cn
(2) storm technology architecture system
storm principle and foundation, message queue Kafka, redis tool, zookeeper detailed explanation, actual combat I: log alarm system project Actual combat 2: guess you like the actual combat of recommender system
stage 4: actual combat of big data projects (real projects of first-line companies)
data acquisition, data processing, data analysis, data presentation, data application
stage 5: big data analysis AI (artificial Intelligence)
data analysis work environment preparation & data analysis basis, data visualization, python machine learning
1 Python machine learning 2. Image recognition & neural network, natural language processing & social network processing, practical project: outdoor equipment recognition and analysis
such an attractive salary is definitely what everyone wants to join. However, the condition for joining is to master certain skills. Based on the requirements of many big data companies, the statistics are as follows:
1
2. Skillfully use Hadoop, M / R, hive, storm and other development tools
3. Familiar with Linux commands and shell programming
4. Sensitive to data, good logical analysis ability, good communication skills and team spirit
5. Familiar with impala, Druid, mdrill, elasticsearch and other big data tools is preferred
according to the requirements of enterprises for big data engineers, the technologies you need to learn are as follows:
stage 1, big data foundation - Java language foundation
(1) Java language foundation
(2) HTML, CSS and JavaScript
(3) JavaWeb and database
stage 2, Linux & Hadoop ecosystem
linux system, Hadoop offline computing outline Distributed database HBase, data warehouse hive, data migration tool sqoop, flume distributed log framework
stage 3, distributed computing framework and spark & strom ecosystem
(1) distributed computing framework
python programming language, Scala programming language, spark big data processing, spark streaming big data processing, spark mlib machine learning, etc Calculation of spark graphx diagram, actual combat 1: recommendation system based on Spark (real project of a front-line company), actual combat 2: sina.com www.sina.com.cn
(2) storm technology architecture system
storm principle and foundation, message queue Kafka, redis tool, zookeeper detailed explanation, actual combat I: log alarm system project Actual combat 2: guess you like the actual combat of recommender system
stage 4: actual combat of big data projects (real projects of first-line companies)
data acquisition, data processing, data analysis, data presentation, data application
stage 5: big data analysis AI (artificial Intelligence)
data analysis work environment preparation & data analysis basis, data visualization, python machine learning
1 Python machine learning 2. Image recognition & neural network, natural language processing & social network processing, practical project: outdoor equipment recognition and analysis
9. The technical strength of conflux is very strong, which is mainly reflected in the realization of high-performance throughput without sacrificing the degree of decentralization
conflux skillfully uses the self-developed scalable consensus algorithm based on tree graph (TG) structure to solve the problem of computing resource waste and security rection caused by bifurcation in high concurrency networks, so that consensus is no longer the bottleneck of blockchain performance. Without sacrificing any degree of decentralization, the high throughput of 3500 + TPS is realized in the internal test network, which is close to visa and other centralized systems in performance.
conflux skillfully uses the self-developed scalable consensus algorithm based on tree graph (TG) structure to solve the problem of computing resource waste and security rection caused by bifurcation in high concurrency networks, so that consensus is no longer the bottleneck of blockchain performance. Without sacrificing any degree of decentralization, the high throughput of 3500 + TPS is realized in the internal test network, which is close to visa and other centralized systems in performance.
10.
You can open the official website of the Supreme People's court, enter it, click the judgment document button in the menu bar, and then enter the relevant conditions to query. Specific query methods are as follows:
1. Search the Supreme People's Court on the Internet, find the official website and click to enter
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