Category Archives: Spark

DataDotz BigData Weekly

DataDotz Bigdata Weekly

Apache Spark
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Structured Streaming in Apache Spark 2.0, it has supported joins (inner join and some type of outer joins) between a streaming and a static DataFrame/Dataset. With the release of Apache Spark 2.3.0, now available in Databricks Runtime 4.0 as part of Databricks Unified Analytics Platform, we now support stream-stream joins. Continue reading

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DataDotz BigData Weekly

DataDotz Bigdata Weekly

Data ingestion into Splunk
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Amazon Web Services (AWS) jointly announced that Amazon Kinesis Data Firehose now supports Splunk Enterprise and Splunk Cloud as a delivery destination. This native integration between Splunk Enterprise, Splunk Cloud, and Amazon Kinesis Data Firehose is designed to make AWS data ingestion setup seamless, while offering a secure and fault-tolerant delivery mechanism. Continue reading

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DataDotz BigData Weekly

DataDotz Bigdata Weekly

Using Amazon S3 with Cloudera BDR
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More of you are moving to public cloud services for backup and disaster recovery purposes, and Cloudera has been enhancing the capabilities of Cloudera Manager and CDH to help you do that. Specifically, Cloudera Backup and Disaster Recovery (BDR) now supports backup to and restore from Amazon S3.BDR lets you replicate HDFS data from your on-premise cluster to or from Amazon S3 with full fidelity (all file and directory metadata is replicated along with the data). Continue reading

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DataDotz BigData Weekly

DataDotz Bigdata Weekly

Server-Side Encryption for Amazon Kinesis Streams
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Amazon Kinesis Streams to ingest, process, and deliver data in real time from millions of devices or applications. Use cases for Kinesis Streams vary, but a few common ones include IoT data ingestion and analytics, log processing, clickstream analytics, and enterprise data bus architectures.Within milliseconds of data arrival, attached to a stream are continuously mining value or delivering data to downstream destinations. Continue reading

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DataDotz BigData Weekly

DataDotz Bigdata Weekly

Apache Kafka
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Spark Streaming integration with Kafka allows users to read messages from a single Kafka topic or multiple Kafka topics. A Kafka topic receives messages across a distributed set of partitions where they are stored. Each partition maintains the messages it has received in a sequential order where they are identified by an offset, also known as a position Continue reading

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