scylla

问题 In Java Spark, I have a dataframe that has a 'bucket_timestamp' column, which represents the time of the bucket that the row belongs to. I want to write the dataframe to a Cassandra DB. The data must be written to the DB with TTL. The TTL should be depended on the bucket timestamp - where each row's TTL should be calculated as ROW_TTL = CONST_TTL - (CurrentTime - bucket_timestamp) , where CONST_TTL is a constant TTL that I configured. Currently I am writing to Cassandra with spark using a

问题 In Java Spark, I have a dataframe that has a 'bucket_timestamp' column, which represents the time of the bucket that the row belongs to. I want to write the dataframe to a Cassandra DB. The data must be written to the DB with TTL. The TTL should be depended on the bucket timestamp - where each row's TTL should be calculated as ROW_TTL = CONST_TTL - (CurrentTime - bucket_timestamp) , where CONST_TTL is a constant TTL that I configured. Currently I am writing to Cassandra with spark using a

问题 Are graph databases more performant than relational databases for highly connected acyclic graph data? I need to significantly speed up my query results and hope that graph databases will be the answer. I had seen significant improvement in my relational database queries when I used Common Table Extensions bringing a recursive search of my sample data from 16 hours to 30 minutes. Still, 30 minutes is way too long for a web application and trying to work around that kind of response gets

问题 While deciding on the technology stack for my own product, I decided to go with scyllaDB for database due to it's impressive performance. For local development, I setup Cassandra on my Macbook. Considering ScyllaDB now supports (experimental) MV (Materialized View), it made the development easy. For dev server, I'm running ScyllaDB on Ubuntu 16.04 hosted on Linod. I am facing following issues : After a few weeks, one day when I deleted an entry from base table (from ScyllaDB running on Ubuntu

问题 I have a table like this in Scylladb. To make it clear I have removed lot of columns from below table but in general this table has ~25 columns total. CREATE TABLE testks.client ( client_id int, lmd timestamp, cola list<text>, colb list<text>, colc boolean, cold int, cole int, colf text, colg set<frozen<colg>>, colh text, PRIMARY KEY (client_id, lmd) ) WITH CLUSTERING ORDER BY (lmd DESC) AND bloom_filter_fp_chance = 0.01 AND caching = {'keys': 'ALL', 'rows_per_partition': 'ALL'} AND comment =

问题 What is the difference between Scylla read path and Cassandra read path? When I stress Cassandra and Scylla then Scylla read performance poor by 5 times than Cassandra using 16 core and normal HDD. I expect better read performance on Scylla compared to Cassandra using normal HDD, because my company doesn't provide SSD's. Can someone please confirm, is it possible to achieve better read performance using normal HDD or not? If yes, what changes required scylla config?. Please guide me! 回答1:

问题 What is the difference between Scylla read path and Cassandra read path? When I stress Cassandra and Scylla then Scylla read performance poor by 5 times than Cassandra using 16 core and normal HDD. I expect better read performance on Scylla compared to Cassandra using normal HDD, because my company doesn't provide SSD's. Can someone please confirm, is it possible to achieve better read performance using normal HDD or not? If yes, what changes required scylla config?. Please guide me! 回答1:

问题 I am playing around with ScyllaDB in docker. To have ScyllaDB operate most efficient in docker production setup it needs a XFS-formatted disk. Do you know how to create a XFS container volumes, file of disk - in Linux and MacOs? Thanks 回答1: The best way to do that is to create a partition or LVM volume, and then format it with xfs normally, using some tool like mkfs.xfs . Once you are done, you can use the -v flag in docker to pass that to your container. 来源： https://stackoverflow.com