Apache Cassandra performance tuning - call for contribution
Dear Apache Cassandra community, we plan to run a large case performance study for Apache Cassandra and MongoDB where the focus is not to compare both systems directly but to answer the question: /how much performance can you get out each DBMS with an optimal configuration compared to the vanilla installation?/ In this study, we use three different configurations of the well-known Yahoo Cloud Serving (YCSB) benchmark to emulate three types of workloads (write-heavy, ready-heavy, mixed). With these workloads, we stress the DBMS’ hosted on AWS EC2. In order to get the optimal answer, we need your support as Apache Cassandra experts to find the optimal OS and DBMS configuration for the outlined workloads (either one general configuration or workload-specific configurations). We will carry out the benchmarks with our Benchmarking-as-a-Service (BaaS) platform and include your configurations into the benchmarking process. And of course, we will release all data as open data sets to the community and publish the study on our website and distribute it through our marketing channels. Moreover, we will reference you in this study and give you the opportunity to introduce yourself and your company as well as comment on the results with your experience and assessment. If you are interested in contributing, feel free to reach out to me. Cheers, Daniel
Re: [EXTERNAL] Availability issues for write/update/read workloads (up to 100s downtime) in case of a Cassandra node failure
Hi Alexander, thanks a lot for the pointers, I checked the mentioned issue. While the reported issue seems to match our problem it only occurs reads and not for writes (according to the Datastax Jira). But we experience downtimes for writes and reads. Which version of the Datastax Driver are you using for your tests? We use version 3.0.0 But I have also tried version 3.2.0 to avoid your mentioned JAVA-1346 issue, but still the same behaviour with respect to the downtime. How is it configured (load balancing policies, etc...) ? Besides the write consistency of ONE it uses the default settings. As we use the YCSB as workload for our experiments, you can have a look at the driver settings in the basic class: https://github.com/brianfrankcooper/YCSB/blob/master/cassandra/src/main/java/com/yahoo/ycsb/db/CassandraCQLClient.java Do you have some debug logs on the client side that could help? On client side the logs shows no exceptions or any suspicious messages. I also turned on the tracing but didn't find any suspicious messages (yet I did not spend too much time in that and I am no expert the Cassandra Driver) If more detailed logs or the traces would help to further investigate the issue let me know and I will rerun the experiments to create the logs and traces. Many thanks again for your help. Cheers, Daniel Am 16.11.2018 um 15:08 schrieb Alexander Dejanovski: Hi Daniel, it seems like the driver isn't detecting that the node went down, which is probably due to the way the node is being killed. If I remember correctly, in some cases Netty transport is still up in the client, which will still allows to send queries without them answering back : https://datastax-oss.atlassian.net/browse/JAVA-1346 Eventually, the node gets discarded when the heartbeat system catches up. It's also possible that the stuck queries then eat up all the available slots in the driver, preventing any other query to be sent in that JVM. Which version of the Datastax Driver are you using for your tests? How is it configured (load balancing policies, etc...) ? Do you have some debug logs on the client side that could help? Thanks, On Fri, Nov 16, 2018 at 1:19 PM Daniel Seybold mailto:daniel.seyb...@uni-ulm.de>> wrote: Hi Sean, thanks for your comments, find below some more details with respect to the (1) VM sizing and (2) the replication factor: (1) VM sizing: We selected the small VMs as intial setup to run our experiments. We have also executed the same experiments (5 nodes) on larger VMs with 6 cores and 12GB memory (where 6GB was allocated to Cassandra). We use the default CMS garbace collector (with default settings) and the debug.log and system.log does not show any suspicious GC messages. (2) Replication factor We set the RF to 5 as we want to emulate a scenario which is able to survive multiple-node failures. We have also tried a RF of 3 (in the 5 node cluster) but the downtime in case of a node failure persists. I also attached two plots which show the results with the downtimes for using the larger VMs and setting the RF to 3 Any further comments much appreciated, Cheers, Daniel Am 09.11.2018 um 19:04 schrieb Durity, Sean R: The VMs’ memory (4 GB) seems pretty small for Cassandra. What heap size are you using? Which garbage collector? Are you seeing long GC times on the nodes? The basic rule of thumb is to give the Cassandra heap 50% of the RAM on the host. 2 GB isn’t very much. Also, I wouldn’t set the replication factor to 5 (the number of nodes). If RF is always equal to the number of nodes, you can’t really scale beyond the size of the disk on any one node (all data is on each node). A replication factor of 3 would be more like a typical production set-up. Sean Durity *From:*Daniel Seybold <mailto:daniel.seyb...@uni-ulm.de> *Sent:* Friday, November 09, 2018 5:49 AM *To:* user@cassandra.apache.org <mailto:user@cassandra.apache.org> *Subject:* [EXTERNAL] Availability issues for write/update/read workloads (up to 100s downtime) in case of a Cassandra node failure Hi Apache Cassandra experts, we are running a set of availability evaluations under a write/read/update workloads with Apache Cassandra and experience some unexpected results, i.e. 0 ops/s over a period up to 100s. In order to provide a clear picture find below the details of (1) the setup and (2) the evaluation workflow *1. Setup:* Cassandra version: 3.11.2 Cluster size: 5 nodes Replication Factor: 5 Each nodes runs in the same private OpenStack based cloud, within the same availability zone and uses the private network. Each nodes runs as OS Ubuntu 16.04 server and has 2 cores, 4GB RAM and 50GB disk. Workload: Yahoo Cloud Serving Benchmark 0.12 W1: 100% write
Re: [EXTERNAL] Availability issues for write/update/read workloads (up to 100s downtime) in case of a Cassandra node failure
Hi Sean, thanks for your comments, find below some more details with respect to the (1) VM sizing and (2) the replication factor: (1) VM sizing: We selected the small VMs as intial setup to run our experiments. We have also executed the same experiments (5 nodes) on larger VMs with 6 cores and 12GB memory (where 6GB was allocated to Cassandra). We use the default CMS garbace collector (with default settings) and the debug.log and system.log does not show any suspicious GC messages. (2) Replication factor We set the RF to 5 as we want to emulate a scenario which is able to survive multiple-node failures. We have also tried a RF of 3 (in the 5 node cluster) but the downtime in case of a node failure persists. I also attached two plots which show the results with the downtimes for using the larger VMs and setting the RF to 3 Any further comments much appreciated, Cheers, Daniel Am 09.11.2018 um 19:04 schrieb Durity, Sean R: The VMs’ memory (4 GB) seems pretty small for Cassandra. What heap size are you using? Which garbage collector? Are you seeing long GC times on the nodes? The basic rule of thumb is to give the Cassandra heap 50% of the RAM on the host. 2 GB isn’t very much. Also, I wouldn’t set the replication factor to 5 (the number of nodes). If RF is always equal to the number of nodes, you can’t really scale beyond the size of the disk on any one node (all data is on each node). A replication factor of 3 would be more like a typical production set-up. Sean Durity *From:*Daniel Seybold *Sent:* Friday, November 09, 2018 5:49 AM *To:* user@cassandra.apache.org *Subject:* [EXTERNAL] Availability issues for write/update/read workloads (up to 100s downtime) in case of a Cassandra node failure Hi Apache Cassandra experts, we are running a set of availability evaluations under a write/read/update workloads with Apache Cassandra and experience some unexpected results, i.e. 0 ops/s over a period up to 100s. In order to provide a clear picture find below the details of (1) the setup and (2) the evaluation workflow *1. Setup:* Cassandra version: 3.11.2 Cluster size: 5 nodes Replication Factor: 5 Each nodes runs in the same private OpenStack based cloud, within the same availability zone and uses the private network. Each nodes runs as OS Ubuntu 16.04 server and has 2 cores, 4GB RAM and 50GB disk. Workload: Yahoo Cloud Serving Benchmark 0.12 W1: 100% write W2: 100% read W3: 100% update *2. Evaluation Workflow: * 1. allocate 5 VMs & deploy DBMS cluster 2. start a YCSB worklod (only one of W1-3) which runs up to 30 minutes 3. wait for 200s 4. trigger the selection of a random node in the cluster and delete the VM without stopping Cassandra before 5. analyze throughput time series over the evaluation *3. (Unexpected) Results *We expected to see a (slight) drop in the throughput as soon as the VM was deleted. But the throughput results show that the there are periods of ~10s - 150s (not deterministic) where no operations are executed (all metrics are collected on client side) Yet, there are no timeout exceptions on client side and also the logs on cluster side do not show anything that explains this behaviour. I attached a series of plots which show the throughput and the downtimes over the evaluation runs. Do you have any explanations for this behaviour or recommendations how to reduce the potential "downtime" ? Thanks in advance for any help and recommendations, Cheers, Daniel -- M.Sc. Daniel Seybold Universität Ulm Institut Organisation und Management von Informationssystemen (OMI) Albert-Einstein-Allee 43 89081 Ulm Phone: +49 (0)731 50-28 799 The information in this Internet Email is confidential and may be legally privileged. It is intended solely for the addressee. Access to this Email by anyone else is unauthorized. If you are not the intended recipient, any disclosure, copying, distribution or any action taken or omitted to be taken in reliance on it, is prohibited and may be unlawful. When addressed to our clients any opinions or advice contained in this Email are subject to the terms and conditions expressed in any applicable governing The Home Depot terms of business or client engagement letter. The Home Depot disclaims all responsibility and liability for the accuracy and content of this attachment and for any damages or losses arising from any inaccuracies, errors, viruses, e.g., worms, trojan horses, etc., or other items of a destructive nature, which may be contained in this attachment and shall not be liable for direct, indirect, consequential or special damages in connection with this e-mail message or its attachment. -- M.Sc. Daniel Seybold Universität Ulm Institut Organisation und Management von Informationssystemen (OMI) Albert-Einstein-Allee 43 89081 Ulm Phone: +49 (0)731 50-28 799 cassandra_failures_v2.p
