import java.sql.{Connection, PreparedStatement, ResultSet} import org.apache.commons.dbcp.BasicDataSource object ConnectPoolUtil { private var bs:BasicDataSource = null /** * 创建数据源 * @return */ def getDataSource():BasicDataSource={ if(bs==null){ bs = new BasicDataSource() bs.setDr...
This post demonstrates how customers, system integrator (SI) partners, and developers can use the serverless streaming ETL capabilities of AWS Glue withAmazon Managed Streaming for Kafka(Amazon MSK) to stream data to a data warehouse such asAmazon Redshift. We also show y...
Getting started with streaming ingestion from Amazon Kinesis Data Streams Getting Started with streaming ingestion from Apache Kafka Authentication with mTLS for Redshift streaming ingestion from Apache Kafka Electric vehicle station-data streaming ingestion tutorial, using Kinesis Data Catalog views Querying ...
Integrating streaming data into Amazon Redshift brings immense value by enabling organizations to harness the potential of real-time analytics and data-driven decision-making. This integration enables you to achieve low latency, measured in seconds, while ingesting hundreds of megabytes ...
Redshift Serverless. This works with Amazon MSK Provisioned and Amazon MSK Serverless, and with Kinesis Data Streams. Amazon Redshift streaming ingestion removes the need to stage a Kinesis Data Streams stream or an Amazon MSK topic in Amazon S3 before ingesting the stream data into Redsh...
This is because the order of the results is not be guaranteed in most common databases and thus different offsets can actually return repeated data. The problem with applying ordering in these queries is a matter of how big your table is, its indexes, etc. For example, InRed...
Leading options for storing streaming data include Amazon S3, Amazon Redshift, and Google Storage. 4. Output for analysis, alerts, real-time applications, data science, and machine learning or AutoML. Once the streaming data has passed through the query or store phase, it can output for ...
StreamXfer is a powerful tool for streaming data from SQL Server to local or object storage(S3) for seamless transfer using UNIX pipe, supporting various general data formats(CSV, TSV, JSON). Supported OS: Linux, macOS I've migrated 10TB data from SQL Server into Amazon Redshift using this...
approach, you store the message in a database or data warehouse and query after you’ve received and stored it. Most companies choose to keep all their data given that the cost of storage is low. Leading options for storing streaming data include Amazon S3, Amazon Redshift, and Google ...
went in reverse order, openinga data exchangeon AWS Marketplace a couple years back, but it's only been adding capabilities forinternal sharing of data for Redshift customers(that required AWS to develop the RA3 instance that finally separated Redshift data into its own pool)...