dependencies for your production and test code dependencies { compile logger,spring,alibaba compile 'org.apache.commons:commons-lang3:3.1' compile "com.fasterxml.jackson.core:jackson- databind:2.9.6" compile netty:netty-tcnative:2.0.18.Final' compile 'com.google.guava:guava:19.0' // web3j依赖 compile 'org.apache.httpcomponents:httpclient:4.5.5', 'org.bouncycastle:bcprov-jdk15on:1.54', 'com.lambdaworks:scrypt:1 为什么使用Phoenix+Hbase Hbase数据模型 Hbase分片基础的Region Hbase在业务实现上存在的不足 Phoenix架构 Phoenix性能对比 Cassandra如何快速、可靠的存储小文件 Cassandra数据的写入 Cassandra数据的读取 总结 区块链存证目前存在的挑战 1. 鉴于目前区块链的发展现状，大数据量的文本、文件信息直接存储在区块 链系统之中会导致系统的处理性能明显下降，并且每个节点都需要有足够

can replace do_work with any other “workhorse” task: $ fab set_hosts:db snapshot $ fab set_hosts:cassandra,cluster2 repair_ring $ fab set_hosts:redis,environ=prod status Failure handling Once the task update(): with cd("/srv/django/myapp"): run("git pull") def reload(): sudo("service apache2 reload") 在三台服务器上并行执行，就像这样： $ fab -H web1,web2,web3 update reload 刚常见的情况是没有启动任何并行执行参数，Fabric 将会按顺序在服务器上执 sudo("service apache2 restart") instance = MyTask() 和下面这个基于函数的任务作用完全一致： @task def deploy(environment, domain="whatever.com"): run("git clone foo") sudo("service apache2 restart") Note how

can replace do_work with any other “workhorse” task: $ fab set_hosts:db snapshot $ fab set_hosts:cassandra,cluster2 repair_ring $ fab set_hosts:redis,environ=prod status Failure handling Once the task update(): with cd("/srv/django/myapp"): run("git pull") def reload(): sudo("service apache2 reload") 在三台服务器上并行执行，就像这样： $ fab -H web1,web2,web3 update reload 刚常见的情况是没有启动任何并行执行参数，Fabric 将会按顺序在服务器上执 sudo("service apache2 restart") instance = MyTask() 和下面这个基于函数的任务作用完全一致： @task def deploy(environment, domain="whatever.com"): run("git clone foo") sudo("service apache2 restart") Note how

order to better handle crash faults. Refer to the official Apache Kafka documentation on upgrading Kafka from previous versions [https://kafka.apache.org/documentation/#upgrade] to upgrade the Kafka cluster afterwards when you have determined your Kafka cluster version. Upgrading Zookeeper An Apache Kafka cluster requires an Apache Zookeeper cluster. The Zookeeper API has been stable for a long time and, as such such, almost any version of Zookeeper is tolerated by Kafka. Refer to the Apache Kafka upgrade [https://kafka.apache.org/documentation/#upgrade] documentation in case there is a specific requirement to upgrade

[https://raft.github.io/raft.pdf]. The other is Kafka [https://kafka.apache.org/] (which uses Zookeeper [https://zookeeper.apache.org/] internally). For information about currently available ordering organizations to contribute nodes to a distributed ordering service. Kafka Similar to Raft-based ordering, Apache Kafka is a CFT implementation that uses a “leader and follower” node configuration. Kafka utilizes ZooKeeper on their own. Likewise, support for Kafka-related issues is handled through Apache [https://kafka.apache.org/], the open-source developer of Kafka, not Hyperledger Fabric. The Fabric Raft implementation

[https://raft.github.io/raft.pdf]. The other is Kafka [https://kafka.apache.org/] (which uses Zookeeper [https://zookeeper.apache.org/] internally). For information about currently available ordering organizations to contribute nodes to a distributed ordering service. Kafka Similar to Raft-based ordering, Apache Kafka is a CFT implementation that uses a “leader and follower” node configuration. Kafka utilizes ZooKeeper on their own. Likewise, support for Kafka-related issues is handled through Apache [https://kafka.apache.org/], the open-source developer of Kafka, not Hyperledger Fabric. The Fabric Raft implementation

[https://raft.github.io/raft.pdf]. The other is Kafka [https://kafka.apache.org/] (which uses Zookeeper [https://zookeeper.apache.org/] internally). For information about currently available ordering organizations to contribute nodes to a distributed ordering service. Kafka Similar to Raft-based ordering, Apache Kafka is a CFT implementation that uses a “leader and follower” node configuration. Kafka utilizes ZooKeeper on their own. Likewise, support for Kafka-related issues is handled through Apache [https://kafka.apache.org/], the open-source developer of Kafka, not Hyperledger Fabric. The Fabric Raft implementation

[https://raft.github.io/raft.pdf]. The other is Kafka [https://kafka.apache.org/] (which uses Zookeeper [https://zookeeper.apache.org/] internally). For information about currently available ordering organizations to contribute nodes to a distributed ordering service. Kafka Similar to Raft-based ordering, Apache Kafka is a CFT implementation that uses a “leader and follower” node configuration. Kafka utilizes ZooKeeper on their own. Likewise, support for Kafka-related issues is handled through Apache [https://kafka.apache.org/], the open-source developer of Kafka, not Hyperledger Fabric. The Fabric Raft implementation

Fabric offers a CFT ordering service implemented with Kafka [https://kafka.apache.org/] and Zookeeper [https://zookeeper.apache.org/]. In subsequent releases, Fabric will deliver a Raft consensus ordering official Apache Kafka documentation on upgrading Kafka from previous versions [https://kafka.apache.org/documentation/#upgrade] to upgrade the Kafka cluster brokers. Upgrading Zookeeper An Apache Kafka cluster requires an Apache Zookeeper cluster. The Zookeeper API has been stable for a long time and, as such, almost any version of Zookeeper is tolerated by Kafka. Refer to the Apache Kafka upgrade [https://kafka

Fabric offers a CFT ordering service implemented with Kafka [https://kafka.apache.org/] and Zookeeper [https://zookeeper.apache.org/]. In subsequent releases, Fabric will deliver a Raft consensus ordering official Apache Kafka documentation on upgrading Kafka from previous versions [https://kafka.apache.org/documentation/#upgrade] to upgrade the Kafka cluster brokers. Upgrading Zookeeper An Apache Kafka cluster requires an Apache Zookeeper cluster. The Zookeeper API has been stable for a long time and, as such, almost any version of Zookeeper is tolerated by Kafka. Refer to the Apache Kafka upgrade [https://kafka