Thanks. I will test copyOnRead. In fact, we do have troubles in using ignite. For we think it uses too much memory. We are finding ways to decrease the memory consumption. I have an idea, but I don't know it is worthy of trying or not. Please advise.
Suppose we have several tables. These tables store some metric data. Each table row contains several dimensions data and metrics. These table share some common dimensions. Currently, we store data like this, each table has all data. And when select no need join: dim_1, ...,dim_x, shared_dim_1,...,shared_dim_n, metric_1,...,metric_m we are going to store like this, we use a separated table to store shared dimensions data: shared_id,shared_dim_1,...,shared_dim_n and each table use a foreign key (shared_id)to refer to the shared table: dim_1,...,dim_x, shared_id,metric_1,...,metric_m This is common ways in RDBMS table design, I don't know whether it works on ignite or not. Also I concern the big overhead each row entry will do can save the memory. Thanks Shawn -----邮件原件----- 发件人: vdpyatkov [mailto:[email protected]] 发送时间: 2016年12月15日 21:36 收件人: [email protected] 主题: Re: how to use memory efficiently Hi, 1) No cache name does not affect the memory utilization. 2) Yes, the key can 3) Ignite stores the description of the class only once, and organizes hash each object. class or field name length does not affect the memory. 4) Off_heap may be cheaper by memory consume, because in some case two copy of entries will stored on heap (on_heap - memory mode)[1]. But ONHEAP_TIERED does not compress data. If you do not going to modify data, which gets from cache, set copyOnRead flag to false: <bean class="org.apache.ignite.configuration.CacheConfiguration"> <property name="copyOnRead" value="false"/> Also, you can try to compress data (before to will put it to cache), but this restricts your SLQ. [1]: https://issues.apache.org/jira/browse/IGNITE-2417 -- View this message in context: http://apache-ignite-users.70518.x6.nabble.com/how-to-use-memory-efficiently -tp9553p9557.html Sent from the Apache Ignite Users mailing list archive at Nabble.com.
