I'm new to Docker so, most likely, I'm missing something.
I'm running a container with Elasticsearch, using this image.
I'm able to setup everyhing correctly. After that I was a using a script developed by a collegue in order to insert some data, basically querying a MySQL database and making HTTP requests .
Problem is, many of those requests get stuck until it fails. If I do netstat -tn | grep 9200
I get:
tcp6 0 0 ::1:58436 ::1:9200 TIME_WAIT
tcp6 0 0 ::1:59274 ::1:9200 TIME_WAIT
...
tcp6 0 0 ::1:58436 ::1:9200 TIME_WAIT
tcp6 0 0 ::1:59274 ::1:9200 TIME_WAIT
with a lot of requests. At this point I'm not sure if it's something related to elastic search or docker. This does not happen if Elasticsearch is instaleld on my machine.
Some info:
$ docker version
Client version: 1.6.2
Client API version: 1.18
Go version (client): go1.4.2
Git commit (client): 7c8fca2
OS/Arch (client): linux/amd64
Server version: 1.6.2
Server API version: 1.18
Go version (server): go1.4.2
Git commit (server): 7c8fca2
OS/Arch (server): linux/amd64
$ docker info
Containers: 6
Images: 103
Storage Driver: devicemapper
Pool Name: docker-252:1-9188072-pool
Pool Blocksize: 65.54 kB
Backing Filesystem: extfs
Data file: /dev/loop0
Metadata file: /dev/loop1
Data Space Used: 4.255 GB
Data Space Total: 107.4 GB
Data Space Available: 103.1 GB
Metadata Space Used: 6.758 MB
Metadata Space Total: 2.147 GB
Metadata Space Available: 2.141 GB
Udev Sync Supported: false
Data loop file: /var/lib/docker/devicemapper/devicemapper/data
Metadata loop file: /var/lib/docker/devicemapper/devicemapper/metadata
Library Version: 1.02.82-git (2013-10-04)
Execution Driver: native-0.2
Kernel Version: 3.14.22-031422-generic
Operating System: Ubuntu 14.04.2 LTS
CPUs: 4
Total Memory: 15.37 GiB
$ docker logs elasticsearch
[2015-06-15 09:10:33,761][INFO ][node ] [Energizer] version[1.6.0], pid[1], build[cdd3ac4/2015-06-09T13:36:34Z]
[2015-06-15 09:10:33,762][INFO ][node ] [Energizer] initializing ...
[2015-06-15 09:10:33,766][INFO ][plugins ] [Energizer] loaded [], sites []
[2015-06-15 09:10:33,792][INFO ][env ] [Energizer] using [1] data paths, mounts [[/usr/share/elasticsearch/data (/dev/mapper/ubuntu--vg-root)]], net usable_space [145.3gb], net total_space [204.3gb], types [ext4]
[2015-06-15 09:10:35,516][INFO ][node ] [Energizer] initialized
[2015-06-15 09:10:35,516][INFO ][node ] [Energizer] starting ...
[2015-06-15 09:10:35,642][INFO ][transport ] [Energizer] bound_address {inet[/0:0:0:0:0:0:0:0:9300]}, publish_address {inet[/172.17.0.5:9300]}
[2015-06-15 09:10:35,657][INFO ][discovery ] [Energizer] elasticsearch/Y1zfiri4QO21zRhcI-bTXA
[2015-06-15 09:10:39,426][INFO ][cluster.service ] [Energizer] new_master [Energizer][Y1zfiri4QO21zRhcI-bTXA][76dea3e6d424][inet[/172.17.0.5:9300]], reason: zen-disco-join (elected_as_master)
[2015-06-15 09:10:39,446][INFO ][http ] [Energizer] bound_address {inet[/0:0:0:0:0:0:0:0:9200]}, publish_address {inet[/172.17.0.5:9200]}
[2015-06-15 09:10:39,446][INFO ][node ] [Energizer] started
[2015-06-15 09:10:39,479][INFO ][gateway ] [Energizer] recovered [0] indices into cluster_state
The important part of the script:
for package in c.fetchall():
id_package, tracking_number, order_number, payment_info, shipment_provider_name, package_status_name=package
el['tracking_number'] = tracking_number
el['order_number'] = order_number
el['payment_info'] = payment_info
el['shipment_provider_name'] = shipment_provider_name
el['package_status_name'] = package_status_name
requests.put("http://localhost:9200/packages/package/%s/_create"%(id_package), json=el)
So, it wasn't a problem with either Docker or Elastic. Just to recap, the same script throwning PUT requests at a Elasticsearch setup locally worked, but when throwning at a container with Elasticsearch failed after a few thousand documents (20k). To note that the overal number of documents was roughtly 800k.
So, what happend? When you setup somethig running on localhost and make a request to it (in this case a PUT request) that request goes through the loopback interface. In pratice ths means that no TCP connection gets created making a lot faster.
When the docker container was setup, ports were bound to the host. Although the script still makes requests to localhost on the desired port, a TCP connection gets created between the host and the docker container through the docker0 interface. This comes at the expense of 2 things:
This is actually a more realistic scenario. We setup Elasticsearch on another machine and did the exact same test and got, as expected, the same result.
The problem was that we were sending to requests and for each of them creating a new connection. Due to the way TCP works, connections cannot be closed immediately. Which meant that we were using all available connections until we got none to use because the rate of creation was higher the actual close rate.
Three suggestions to fix this:
Connection: close
header: option for the sender to signal that the connection will be closed after completion of the response.I ended up going with option 3) and rewrote my collegue's script and reusing the same TCP connection.
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