Hi, Camel does support the concepts of streaming and stream caching. A stream cache will make a stream readable multiple times. For this purpose it stores the message payload either in memory or in a temporary file (and the whole concept is transparent for the camel components).
See http://camel.apache.org/stream-caching.html for details. Finally you need your bean to support this by writing your output into a CachedOutputStream and then setting the StreamCache you get from it as message body. Best regards Stephan -----Original Message----- From: Goyal, Arpit [mailto:[email protected]] Sent: Samstag, 10. März 2018 06:48 To: [email protected] Subject: Changing large in-memory data to file based operation Hello Camel Experts, Currently we have something of below route (as simplified version), where we keep reading records 1000 at a time and keep formatting and holding in memory. Current Simplified Solution: from("direct:processing") .bean(<formatRecordsAndAddToBody>) .choice() .when(header(<isMoreRecords>).bean(<readMoreRecords>).to("direct:processing") .otherwise().to("sftp:///";) Generally the data is small and we kept in-memory, we want to improve the same now to safe-guard any in-memory problem. In our landscape we can use 'tmp' storage to hold the file. So we plan to change it like this Possible Modified Solution: from("direct:processing") .bean(<formatRecordsAndAddToTmpFile>) .choice() .when(header(<isMoreRecords>).bean(<readMoreRecords>).to("direct:processing") .otherwise().bean(<readTmpFile&SetAsBody>).to("sftp:///";) When locally tried the solution, we see it works - Camel understand 'java.io.File' object & writes to SFTP. Question 1 - Would camel load it in memory completely before writing to SFTP? Question 2 - If yes, how can we solve this problem - does some way of streaming works? Checked : http://www.catify.com/2012/07/09/parsing-large-files-with-apache-camel/ already but they are holding in memory. Limitation: We don't want to write in chunks to sftp because of the complexity of some data have to written out-of-order. Regards, Arpit.
