AWS DataSync

AWS DataSync is an online data transfer service that simplifies, automates, and accelerates copying large amounts of data to and from AWS storage services over the internet or AWS Direct Connect. DataSync can copy data between Network File System (NFS), Server Message Block (SMB) file servers, self-managed object storage, or AWS Snowcone, and Amazon Simple Storage Service (Amazon S3) buckets, Amazon Elastic File System (Amazon EFS) file systems, and Amazon FSx for Windows File Server file systems.

DataSync includes encryption and integrity validation to help make sure your data arrives securely, intact. DataSync does both full initial copies, and incremental transfers of changing data. 

Comments

Post a Comment

Popular posts from this blog

SQL

Joins - Not always very obvious ( Following example uses Hive ). create table x_temp ( name string, p_date int  ) insert into x_temp(name,p_date) values ('x1',20181025),('x2', 20181026), ('x3',20181027) create table y_temp ( name string, s_date int  ) insert into y_temp(name,s_date) values ('x1',20181025),('x2', 20181026), ('x3',20181027) create table z_temp ( name string, p_date int, s_date int ) insert into z_temp(name,p_date,s_date) values ('z1','20181025','20181025') select x.*, y.* from x_temp x, y_temp y, z_temp z  where x.p_date != z.p_date and  y.s_date != z.s_date) generates 4 records... x.name,x.p_date,y.name,y.s_date x2, 20181026, x2, 20181026 x3, 20181027, x2, 20181026 x2, 20181026, x3, 20181027 x3, 20181027, x3, 20181027 select x.*, y.* from x_temp x, y_temp y, z_temp z  where x.p_date != z.p_date or  y.s_date != z.s_date) generates 8 records x.name,x.p_date,y.
Read more

Analytics

Types of Analytics ( Notes from AWS Course )  Descriptive - What happened ?  hindsight  Diagnostic - Why did it  happen?  hindsight & insight  Predictive  - What will happen ? insight & foresight  Prescriptive - What should I do ? foresight  Cognitive & AI  - What are recommended actions ? foresight & hypothesis input  Popular BI Tools:  https://www.cio.com/article/3284415/10-bi-tools-for-data-visualization.html
Read more

HIVE

1. When doing multi table joins, except the last ( right most ) table, other tables are buffered in the reducers. So to have less memory footprint on reducers, largest tables should be the last one as it is not buffered but streamed to reducers.   For Impala , it is different. 2.  You can filter the unwanted records within the join itself. SELECT  a.*,   b. * FROM a LEFT OUTER JOIN b ON ( a.key=b.key  AND  b.name= 'Tim'   AND a .name= 'Kim' ) 3. Joins are left associative. So execution happens from left to right and the result of joins is  fed into next join operation. 4. To find the value of variable     set hive.execution.engine 5. To find values of all variables set  6. If you want to pass different hive configuration settings in hive shell, you can use --hiveconf. For example hive --hiveconf hivi.optimize.sort.dynamic.partition=true --hiveconf hive.exec.dynamic.partition.mode=nonstrict 7.  In case you accidentally drop the p
Read more