High Performance Data Storage in a Microservices Environment

HIGH PERFORMANCE DATA STORAGE IN A
MICROSERVICES ENVIRONMENT

MICROSERVICES & DATA STORAGE
2

JBOSS DATA GRID IN-MEMORY DATA STORE
ACCELERATE BIG DATA ANALYTICS
7
In-memory data platform
BRMS Spark EAPHadoop
Spring
Boot
etc.
Cassandra
/ Red Hat
Storage
Data Overﬂow Mgmt.
to Persistence Store
(Hydration & Dehydration)
RDD/DStream Map-Reduce
Java Stream
In-
memory
Analytics
and
Compute
Grid
Application Frameworks
& APIs

GET VALUE OUT OF YOUR DATA
9
APACHE SPARK MICROSERVICES BUSINESS REPORTING

11INSERT DESIGNATOR, IF NEEDED

String query =
"SELECT displayName, reputation FROM users ORDER BY
reputation DESC LIMIT 10";

List<Row> rows = sqlContext.sql(query).collectAsList();
InfinispanJavaRDD.write(rows,properties);

String query =
"SELECT u.location as `Location`,count(p.id) as `Posts` "
+ "FROM users u "
+ "INNER JOIN posts p ON u.id=p.ownerUserId "
+ "WHERE p.postTypeId=1 "
+ "GROUP BY u.location ”
+ "ORDER BY `Posts` DESC LIMIT 10";

List<Row> rows = sqlContext.sql(query).collectAsList();

highestReputation
keyword
KeywordAnalytics
HighestRankAnalytics
DEMO DATA
PostStore
UserStore
owner = 2, dist_sync

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High Performance Data Storage in a Microservices Environment

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High Performance Data Storage in a Microservices Environment