# AeroSpark read performance

**URL:** https://discuss.aerospike.com/t/aerospark-read-performance/3264
**Category:** Spark
**Tags:** query, spark
**Created:** [August 10, 2016, 7:38am UTC](https://discuss.aerospike.com/t/aerospark-read-performance/3264 "2016-08-10T07:38:13Z")
**Posts on this page:** 1
**Page:** 1

<div class="post-metadata">

### Author: ![Vadim\_Dobroskok](https://avatars.discourse-cdn.com/v4/letter/v/97f17d/32.png) [@Vadim\_Dobroskok](https://discuss.aerospike.com/u/Vadim_Dobroskok)
#### Post date: [August 10, 2016, 7:38am UTC](https://discuss.aerospike.com/t/aerospark-read-performance/3264/1 "2016-08-10T07:38:13Z")

</div>

I am using latest AeroSpark connector to work with Spark ML. But when i have inserted round 60M records to AeroSpike, i got too big time amount in read operations. For example for fetch round 500K records from set that contains 60M records, AeroSpark spend ~30 mins. When i look at htop cmd output, AeroSpike use only 7% of CPU.

How can i speed up performance in read operations? Seems AeroSpark is working only by one thread, how i can parallelize this job? Any suggestions?

AeroSpike conf: memory-size 8G # Maximum memory allocation for data and  
default-ttl 30d

```
storage-engine device { # Configure the storage-engine to use                                                                                                                                       
    file /vol/rmla.data # Location of data file on server.                                                                                                                                          
    filesize 900G # Max size of each file in GiB.                                                                                                                                             

```

}