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Re: [geomesa-users] GeoMesa range query performance

I used concurrent threads. 1 thread for 1 query.

On Mon, May 20, 2019, 6:00 AM Emilio Lahr-Vivaz <elahrvivaz@xxxxxxxx> wrote:
Hello,

How are you submitting queries to GeoMesa?

Thanks,

Emilio

On 5/19/19 3:25 PM, Tin Vu wrote:
Hi Emilio,

Thanks for your response. I executed my experiments as follows:
1. Cluster: 1 master node, 12 slave nodes, 64 GB memory in each node.
2. Dataset: Open street map All Nodes (size 96 GB, 2.7 Billion records).
3. Queries: I created 10 batches of queries with different size (for example, query area / whole space area = 10^-12, 10^-11,...., 10^-2). Each batch contains 100 square query in the same size. Those query is randomly distributed in the whole space.
4. I submit those batches of queries to SpatialHadoop and GeoMesa, wait until they finish then count the running time.

Thanks,

Tin


On Thu, May 16, 2019 at 2:16 PM Emilio Lahr-Vivaz <elahrvivaz@xxxxxxxx> wrote:
Hello,

Could you say more about how you're querying? SpatialHadoop uses map/reduce jobs, if I understand - it seems like there would be a lot of overhead to spin up the job. How long are your queries taking? How big is your cluster?

Thanks,

Emilio

On 5/16/19 3:20 PM, Tin Vu wrote:
Hi all,

I just wanted to to ask you a question about the performance of GeoMesa range query. This is my experimental set up:
1. Systems: GeoMesa on Accumulo, SpatialHadoop (http://spatialhadoop.cs.umn.edu/)
2. Dataset: All node dataset fromÂhttp://spatialhadoop.cs.umn.edu/datasets.html, with 96GB and 2.7 billions points.
3. Query: range query with different selectivity: 10^-12, 10^-11, 10^-10, which is the ratio of query range and total area of the dataset space.

I saw that GeoMesa does not work better than SpatialHadoop, which is not expected. Since I think that GeoMesa (organize data in record-level) should be better than SpatialHadoop (organize data in block-level) in highly selective queries. Could you tell me any idea to tune GeoMesa such that it can provide a better performance?

Thanks,

Tin

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