Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 1 / 39Helmut Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 2 / 39 About Myself • Professor ComputingHelmut Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 3 / 39 Creating Game Engines with C++ • Vienna Game Job System + • Graphics API Abstraction Layer + • Vienna Entity Engine 2.0 https://github.com/hlavacs 20Helmut Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 4 / 39 The Game Loop auto prev = high_resolution_clock::now(); while( !finished()

Batch Norm 主讲人：龙良曲 Intuitive explanation Intuitive explanation Feature scaling ▪ Image Normalization ▪ Batch Normalization Batch Norm https://medium.com/syncedreview/facebook-ai-proposes-group-normalization- p-normalization- alternative-to-batch-normalization-fb0699bffae7 Pipeline nn.BatchNorm2d Class variables Test Visualization Advantages ▪ Converge faster ▪ Better performance ▪ Robust ▪ stable

Tianyi(Tanki) Zhang tankiistanki tankijong COROUTINE JOB SYSTEM WITHOUT STANDARD LIBRARY source code of the system: https://github.com/tankiJong/cpp-coroutine-job-system Hi Everyone, Tanki here. Thanks for coming We will see them many times in the rest of the talk, and they will have different names in the job system. 1314 14 template struct task; task sum(int a, int b) { int result = a customization. 4344 44 JOB SYSTEM • Scheduler + User defined workload • Optimize for CPU throughput Okay, finally, we are ready to talk about the job system! What is a job system? Job system is a kind of

Doris 中。 目前仅支持通过无认证或者 SSL 认证方式，从 Kakfa 导入 CSV 或 Json 格式的数据。 语法： 导入作业的名称，在同一个 database 内，相同名称只能有一个 job 在运行。 指定需要导入的表的名称。 数据合并类型。默认为 APPEND，表示导入的数据都是普通的追加写操作。MERGE 和 DELETE 类型仅适用于 Unique Key 模 型表。其中 MERGE ROUTINE ROUTINE LOAD LOAD [[db db..]]job_name job_name ON ON tbl_name tbl_name [[merge_type merge_type]] [[load_properties load_properties]] [[job_properties job_properties]] FROM FROM data_source data_source data_source [[data_source_properties data_source_properties]] [db.]job_name [db.]job_name tbl_name tbl_name merge_type merge_type [column_separator], [column_separator], [columns_mapping], [columns_mapping]

spark.SparkContext: Starting job: collect at ExecuteStatement.scala:97 2021-10-28 13:56:27.639 INFO kyuubi.SQLOperationListener: Query [a46ca504-fe3a-4dfb-be1e-19770af8ac4c]: Job 3 started with 1 stages, started with 1 tasks, 1 active stages running 2021-10-28 13:56:27.651 INFO scheduler.DAGScheduler: Job 3 finished: collect at ExecuteStatement.scala:97, took 0.016234 s 2021-10-28 13:56:27.653 INFO kyuubi 2021-10-28 13:56:27.674 INFO kyuubi.SQLOperationListener: Query [a46ca504-fe3a-4dfb-be1e-19770af8ac4c]: Job 3 succeeded, 0 active jobs running 2021-10-28 13:56:27.744 INFO operation.ExecuteStatement: Processing

spark.SparkContext: Starting job: collect at ExecuteStatement.scala:97 2021-10-28 13:56:27.639 INFO kyuubi.SQLOperationListener: Query [a46ca504-fe3a-4dfb-be1e-19770af8ac4c]: Job 3 started with 1 stages, started with 1 tasks, 1 active stages running 2021-10-28 13:56:27.651 INFO scheduler.DAGScheduler: Job 3 finished: collect at ExecuteStatement.scala:97, took 0.016234 s 2021-10-28 13:56:27.653 INFO kyuubi 2021-10-28 13:56:27.674 INFO kyuubi.SQLOperationListener: Query [a46ca504-fe3a-4dfb-be1e-19770af8ac4c]: Job 3 succeeded, 0 active jobs running 2021-10-28 13:56:27.744 INFO operation.ExecuteStatement: Processing

· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 6118 17.2.1 Batch Create Table · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · times faster for creating tables in batch (experimental) 36 With the implementation of the new DDL architecture in v7.6.0, the �→ performance of batch table creation has witnessed a remarkable Compared with previous versions, the new version of the DDL improves the performance of creating batch tables by 10 times, and significantly reduces time for creating tables. For more information, see

· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 6015 17.2.1 Batch Create Table · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · shared object storage (Amazon S3 in this �→ first iteration) to store intermediary files during the job, adding �→ flexibility and cost savings. Operations like ADD INDEX �→ and IMPORT returns Can't find column for queries with GROUP_CONCAT #41957 @AilinKid • Fix the panic issue of batch-client in client-go #47691 @crazycs520 • Fix the issue of incorrect memory usage estimation in IN