Confluent

JUNE 13, 2019

This data pipeline is a great example of a use case for Apache Kafka ®. The data processing pipeline characterizes these objects, deriving key parameters such as brightness, color, ellipticity, and coordinate location, and broadcasts this information in alert packets. The case for Apache Kafka. Astronomy in real time.

Kafka 102

Kafka Python Bytes Data Pipeline 102

Confluent

APRIL 30, 2019

With the release of Apache Kafka ® 2.1.0, Kafka Streams introduced the processor topology optimization framework at the Kafka Streams DSL layer. This framework opens the door for various optimization techniques from the existing data stream management system (DSMS) and data stream processing literature.

Kafka 91

Kafka Coding Process Software Engineer 91

Confluent

SEPTEMBER 27, 2019

Today, nearly everyone uses standard data formats like Avro, JSON, and Protobuf to define how they will communicate information between services within an organization, either synchronously through RPC calls or asynchronously through Apache Kafka ® messages. To allow Schema Validation on write, Confluent Server must be schema aware.

Kafka 16

Kafka Data Governance Bytes Government 16

ProjectPro

NOVEMBER 22, 2021

show(truncate=False) #Drop duplicates on selected columns dropDisDF = df.dropDuplicates(["department","salary"]) print("Distinct count of department salary : "+str(dropDisDF.count())) dropDisDF.show(truncate=False) } Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Q6.

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40