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*: update ETL description (#671)

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lilin90 authored and CaitinChen committed Oct 16, 2018
1 parent 2524611 commit dba84f67324c683fbf139fe4393cd988dd7786dd
Showing with 3 additions and 3 deletions.
  1. +1 −1 README.md
  2. +1 −1 overview.md
  3. +1 −1 tispark/tispark-user-guide.md
@@ -188,7 +188,7 @@ TiDB (The pronunciation is: /'taɪdiːbi:/ tai-D-B, etymology: titanium) is an o
TiDB is designed to work in the cloud -- public, private, or hybrid -- making deployment, provisioning, and maintenance drop-dead simple.
- __No more ETL__
- __Minimize ETL__
ETL (Extract, Transform and Load) is no longer necessary with TiDB's hybrid OLTP/OLAP architecture, enabling you to create new values for your users, easier and faster.
@@ -24,7 +24,7 @@ TiDB (The pronunciation is: /'taɪdiːbi:/ tai-D-B, etymology: titanium) is an o
TiDB is designed to work in the cloud -- public, private, or hybrid -- making deployment, provisioning, and maintenance drop-dead simple.
- __No more ETL__
- __Minimize ETL__
ETL (Extract, Transform and Load) is no longer necessary with TiDB's hybrid OLTP/OLAP architecture, enabling you to create new values for your users, easier and faster.
@@ -18,7 +18,7 @@ TiSpark is an OLAP solution that runs Spark SQL directly on TiKV, the distribute
+ TiSpark integrates with Spark Catalyst Engine deeply. It provides precise control of the computing, which allows Spark read data from TiKV efficiently. It also supports index seek, which improves the performance of the point query execution significantly.
+ It utilizes several strategies to push down the computing to reduce the size of dataset handling by Spark SQL, which accelerates the query execution. It also uses the TiDB built-in statistical information for the query plan optimization.
+ From the data integration point of view, TiSpark and TiDB serve as a solution runs both transaction and analysis directly on the same platform without building and maintaining any ETLs. It simplifies the system architecture and reduces the cost of maintenance.
+ From the data integration point of view, TiSpark and TiDB serve as a solution for running both transaction and analysis directly on the same platform without building and maintaining any ETLs. It simplifies the system architecture and reduces the cost of maintenance.
+ also, you can deploy and utilize tools from the Spark ecosystem for further data processing and manipulation on TiDB. For example, using TiSpark for data analysis and ETL; retrieving data from TiKV as a machine learning data source; generating reports from the scheduling system and so on.
## Environment setup

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