ARTS - 2019 Week 7-4¶
- 94. Binary Tree Inorder Traversal
- 144. Binary Tree Preorder Traversal
- 145. Binary Tree Postorder Traversal
Building the next generation Spark SQL engine at speed poses new challenges to both automation and testing. At Databricks, we are implementing a new testing framework for assessing the quality and performance of new developments as they produced. Having more than 1,200 worldwide contributors, Apache Spark follows a rapid pace of development. At this scale, new testing tooling such as random query and data generation, fault injection, longevity stress, and scalability tests are essential to guarantee a reliable and performance Spark later in production. By applying such techniques, we will demonstrate the effectiveness of our testing infrastructure by drilling-down into cases where correctness and performance regressions have been found early. In addition, showing how they have been root-caused and fixed to prevent regressions in production and boosting the continuous delivery of new features.
making high quality releases automatic and frequent
- scan 设置合理的缓存：scan.setCaching(1000);
- get 使用批量请求方式：hTable.get(getList);