ElasticSearch Out of Memory

时间:2016-01-04 23:23:12

标签: elasticsearch out-of-memory

我有一个基于Symfony2.6的博客(30篇小文章),并在一个小的Ubuntu14.04 VPS(4GB内存,50GB磁盘空间)上运行。我使用ElasticSearch抛出FOS ElasticaBundle,以允许用户/读者在这个博客上查找文章(通过关键字和类别,就是它)。

近2个月一切顺利,现在似乎博客完全无法使用!

我发现这是由于某种" OOM"问题

我试图将indices.fieddata.cache.size设置为40%。

我试过看一下head插件。它回答说集群没有连接。

我试过/ _nodes / stats / indices / fielddata?fields = * request。谈到用于此节点的5572个字节,这看起来并不多。

当我尝试在终端中使用Ctrl + C停止节点时,需要很长时间,它会打印:

  

[2016-01-04 23:38:37,085] [INFO] [节点] [11月]   停止...线程中的异常" elasticsearch [Novs] [generic] [T#4]"   java.lang.OutOfMemoryError:Java堆空间

我还发现我的elasticsearch1 .... / data文件夹绝对是huuge,大约26GB。我很快就会耗尽磁盘空间,并且不知道我是否可以手动删除旧文件夹。例如。

是否有任何简单的命令行工具可以在几秒钟内帮助摆脱所有这些OOM问题?或类似的东西?

ElasticSearch配置(我唯一能在/elastiseach-1.7.3/config/中找到的配置):

##################### Elasticsearch Configuration Example 

#####################

# This file contains an overview of various configuration settings,
# targeted at operations staff. Application developers should
# consult the guide at <elasticsearch.org/guide>.
#
# The installation procedure is covered at
# <elasticsearch.org/guide/en/elasticsearch/reference/current/setup.html>.
#
# Elasticsearch comes with reasonable defaults for most settings,
# so you can try it out without bothering with configuration.
#
# Most of the time, these defaults are just fine for running a production
# cluster. If you're fine-tuning your cluster, or wondering about the
# effect of certain configuration option, please _do ask_ on the
# mailing list or IRC channel [elasticsearch.org/community].

# Any element in the configuration can be replaced with environment variables
# by placing them in ${...} notation. For example:
#
#node.rack: ${RACK_ENV_VAR}

# For information on supported formats and syntax for the config file, see
# <elasticsearch.org/guide/en/elasticsearch/reference/current/setup-configuration.html>


################################### Cluster ###################################

# Cluster name identifies your cluster for auto-discovery. If you're running
# multiple clusters on the same network, make sure you're using unique names.
#
#cluster.name: elasticsearch


#################################### Node #####################################

# Node names are generated dynamically on startup, so you're relieved
# from configuring them manually. You can tie this node to a specific name:
#
#node.name: "Franz Kafka"

# Every node can be configured to allow or deny being eligible as the master,
# and to allow or deny to store the data.
#
# Allow this node to be eligible as a master node (enabled by default):
#
#node.master: true
#
# Allow this node to store data (enabled by default):
#
#node.data: true

# You can exploit these settings to design advanced cluster topologies.
#
# 1. You want this node to never become a master node, only to hold data.
#    This will be the "workhorse" of your cluster.
#
#node.master: false
#node.data: true
#
# 2. You want this node to only serve as a master: to not store any data and
#    to have free resources. This will be the "coordinator" of your cluster.
#
#node.master: true
#node.data: false
#
# 3. You want this node to be neither master nor data node, but
#    to act as a "search load balancer" (fetching data from nodes,
#    aggregating results, etc.)
#
#node.master: false
#node.data: false

# Use the Cluster Health API [localhost:9200/_cluster/health], the
# Node Info API [localhost:9200/_nodes] or GUI tools
# such as <http://www.elasticsearch.org/overview/marvel/>,
# <github.com/karmi/elasticsearch-paramedic>,
# <github.com/lukas-vlcek/bigdesk> and
# mobz.github.com/elasticsearch-head> to inspect the cluster state.

# A node can have generic attributes associated with it, which can later be used
# for customized shard allocation filtering, or allocation awareness. An attribute
# is a simple key value pair, similar to node.key: value, here is an example:
#
#node.rack: rack314

# By default, multiple nodes are allowed to start from the same installation location
# to disable it, set the following:
#node.max_local_storage_nodes: 1


#################################### Index ####################################

# You can set a number of options (such as shard/replica options, mapping
# or analyzer definitions, translog settings, ...) for indices globally,
# in this file.
#
# Note, that it makes more sense to configure index settings specifically for
# a certain index, either when creating it or by using the index templates API.
#
# See <elasticsearch.org/guide/en/elasticsearch/reference/current/index-modules.html> and
# <elasticsearch.org/guide/en/elasticsearch/reference/current/indices-create-index.html>
# for more information.

# Set the number of shards (splits) of an index (5 by default):
#
#index.number_of_shards: 5

# Set the number of replicas (additional copies) of an index (1 by default):
#
#index.number_of_replicas: 1

# Note, that for development on a local machine, with small indices, it usually
# makes sense to "disable" the distributed features:
#
#index.number_of_shards: 1
#index.number_of_replicas: 0

# These settings directly affect the performance of index and search operations
# in your cluster. Assuming you have enough machines to hold shards and
# replicas, the rule of thumb is:
#
# 1. Having more *shards* enhances the _indexing_ performance and allows to
#    _distribute_ a big index across machines.
# 2. Having more *replicas* enhances the _search_ performance and improves the
#    cluster _availability_.
#
# The "number_of_shards" is a one-time setting for an index.
#
# The "number_of_replicas" can be increased or decreased anytime,
# by using the Index Update Settings API.
#
# Elasticsearch takes care about load balancing, relocating, gathering the
# results from nodes, etc. Experiment with different settings to fine-tune
# your setup.

# Use the Index Status API (<localhost:9200/A/_status>) to inspect
# the index status.

#################################### Paths ####################################

# Path to directory containing configuration (this file and logging.yml):
#
#path.conf: /path/to/conf

# Path to directory where to store index data allocated for this node.
#
#path.data: /path/to/data
#
# Can optionally include more than one location, causing data to be striped across
# the locations (a la RAID 0) on a file level, favouring locations with most free
# space on creation. For example:
#
#path.data: /path/to/data1,/path/to/data2

# Path to temporary files:
#
#path.work: /path/to/work

# Path to log files:
#
#path.logs: /path/to/logs

# Path to where plugins are installed:
#
#path.plugins: /path/to/plugins


#################################### Plugin ###################################

# If a plugin listed here is not installed for current node, the node will not start.
#
#plugin.mandatory: mapper-attachments,lang-groovy


################################### Memory ####################################

# Elasticsearch performs poorly when JVM starts swapping: you should ensure that
# it _never_ swaps.
#
# Set this property to true to lock the memory:
#
#bootstrap.mlockall: true

# Make sure that the ES_MIN_MEM and ES_MAX_MEM environment variables are set
# to the same value, and that the machine has enough memory to allocate
# for Elasticsearch, leaving enough memory for the operating system itself.
#
# You should also make sure that the Elasticsearch process is allowed to lock
# the memory, eg. by using `ulimit -l unlimited`.


############################## Network And HTTP ###############################

# Elasticsearch, by default, binds itself to the 0.0.0.0 address, and listens
# on port [9200-9300] for HTTP traffic and on port [9300-9400] for node-to-node
# communication. (the range means that if the port is busy, it will automatically
# try the next port).

# Set the bind address specifically (IPv4 or IPv6):
#
#network.bind_host: 192.168.0.1

# Set the address other nodes will use to communicate with this node. If not
# set, it is automatically derived. It must point to an actual IP address.
#
#network.publish_host: 192.168.0.1

# Set both 'bind_host' and 'publish_host':
#
#network.host: 192.168.0.1

# Set a custom port for the node to node communication (9300 by default):
#
#transport.tcp.port: 9300

# Enable compression for all communication between nodes (disabled by default):
#
#transport.tcp.compress: true

# Set a custom port to listen for HTTP traffic:
#
#http.port: 9200

# Set a custom allowed content length:
#
#http.max_content_length: 100mb

# Disable HTTP completely:
#
#http.enabled: false


################################### Gateway ###################################

# The gateway allows for persisting the cluster state between full cluster
# restarts. Every change to the state (such as adding an index) will be stored
# in the gateway, and when the cluster starts up for the first time,
# it will read its state from the gateway.

# There are several types of gateway implementations. For more information, see
# <elasticsearch.org/guide/en/elasticsearch/reference/current/modules-gateway.html>.

# The default gateway type is the "local" gateway (recommended):
#
#gateway.type: local
# Settings below control how and when to start the initial recovery process on
# a full cluster restart (to reuse as much local data as possible when using shared
# gateway).

# Allow recovery process after N nodes in a cluster are up:
#
#gateway.recover_after_nodes: 1

# Set the timeout to initiate the recovery process, once the N nodes
# from previous setting are up (accepts time value):
#
#gateway.recover_after_time: 5m

# Set how many nodes are expected in this cluster. Once these N nodes
# are up (and recover_after_nodes is met), begin recovery process immediately
# (without waiting for recover_after_time to expire):
#
#gateway.expected_nodes: 2


############################# Recovery Throttling #############################

# These settings allow to control the process of shards allocation between
# nodes during initial recovery, replica allocation, rebalancing,
# or when adding and removing nodes.

# Set the number of concurrent recoveries happening on a node:
#
# 1. During the initial recovery
#
#cluster.routing.allocation.node_initial_primaries_recoveries: 4
#
# 2. During adding/removing nodes, rebalancing, etc
#
#cluster.routing.allocation.node_concurrent_recoveries: 2

# Set to throttle throughput when recovering (eg. 100mb, by default 20mb):
#
#indices.recovery.max_bytes_per_sec: 20mb

# Set to limit the number of open concurrent streams when
# recovering a shard from a peer:
#
#indices.recovery.concurrent_streams: 5


################################## Discovery ##################################

# Discovery infrastructure ensures nodes can be found within a cluster
# and master node is elected. Multicast discovery is the default.

# Set to ensure a node sees N other master eligible nodes to be considered
# operational within the cluster. This should be set to a quorum/majority of
# the master-eligible nodes in the cluster.
#
#discovery.zen.minimum_master_nodes: 1

# Set the time to wait for ping responses from other nodes when discovering.
# Set this option to a higher value on a slow or congested network
# to minimize discovery failures:
#
#discovery.zen.ping.timeout: 3s

# For more information, see
# <elasticsearch.org/guide/en/elasticsearch/reference/current/modules-discovery-zen.html>

# Unicast discovery allows to explicitly control which nodes will be used
# to discover the cluster. It can be used when multicast is not present,
# or to restrict the cluster communication-wise.
#
# 1. Disable multicast discovery (enabled by default):
#
#discovery.zen.ping.multicast.enabled: false
#
# 2. Configure an initial list of master nodes in the cluster
#    to perform discovery when new nodes (master or data) are started:
#
#discovery.zen.ping.unicast.hosts: ["host1", "host2:port"]

# EC2 discovery allows to use AWS EC2 API in order to perform discovery.
#
# You have to install the cloud-aws plugin for enabling the EC2 discovery.
#
# For more information, see
# <elasticsearch.org/guide/en/elasticsearch/reference/current/modules-discovery-ec2.html>
#
# See <http://elasticsearch.org/tutorials/elasticsearch-on-ec2/>
# for a step-by-step tutorial.

# GCE discovery allows to use Google Compute Engine API in order to perform discovery.
#
# You have to install the cloud-gce plugin for enabling the GCE discovery.
#
# For more information, see <github.com/elasticsearch/elasticsearch-cloud-gce>.

# Azure discovery allows to use Azure API in order to perform discovery.
#
# You have to install the cloud-azure plugin for enabling the Azure discovery.
#
# For more information, see <github.com/elasticsearch/elasticsearch-cloud-azure>.

################################## Slow Log ##################################

# Shard level query and fetch threshold logging.

#index.search.slowlog.threshold.query.warn: 10s
#index.search.slowlog.threshold.query.info: 5s
#index.search.slowlog.threshold.query.debug: 2s
#index.search.slowlog.threshold.query.trace: 500ms

#index.search.slowlog.threshold.fetch.warn: 1s
#index.search.slowlog.threshold.fetch.info: 800ms
#index.search.slowlog.threshold.fetch.debug: 500ms
#index.search.slowlog.threshold.fetch.trace: 200ms

#index.indexing.slowlog.threshold.index.warn: 10s
#index.indexing.slowlog.threshold.index.info: 5s
#index.indexing.slowlog.threshold.index.debug: 2s
#index.indexing.slowlog.threshold.index.trace: 500ms

################################## GC Logging ################################

#monitor.jvm.gc.young.warn: 1000ms
#monitor.jvm.gc.young.info: 700ms
#monitor.jvm.gc.young.debug: 400ms

#monitor.jvm.gc.old.warn: 10s
#monitor.jvm.gc.old.info: 5s
#monitor.jvm.gc.old.debug: 2s

################################## Security ################################

# Uncomment if you want to enable JSONP as a valid return transport on the
# http server. With this enabled, it may pose a security risk, so disabling
# it unless you need it is recommended (it is disabled by default).
#
#http.jsonp.enable: true

提前感谢您的帮助。

1 个答案:

答案 0 :(得分:14)

由于这似乎是Heap Space问题,请确保您有足够的内存。阅读有关堆大小调整的this blog

因为你有4GB的RAM将其中的一半分配给Elasticsearch堆。运行export ES_HEAP_SIZE=2g。同时锁定JVM的内存,在配置文件中取消注释bootstrap.mlockall: true

另一个重要的事情是,如果你只有30篇小文章,你的data folder 26GB大小怎么样?你有多少个索引,运行GET _cat/indices来检查哪个索引占用了那么多空间。运行GET /_nodes/stats以查看有关节点的详细信息,您可能能够找出问题所在。还有一件事,如果你使用marvel plugin,那么marvel indices非常庞大,你需要将它们删除以释放磁盘空间。

调整indices.fieddata.cache.size不是缺乏记忆的解决方案。来自Docs

  

此设置是一种安全措施,而不是内存不足的解决方案。

     

如果您没有足够的内存来保存您的fielddata   内存,Elasticsearch将不断从磁盘重新加载数据,   并驱逐其他数据以腾出空间。驱逐导致重磁盘I / O和   在内存中生成大量垃圾,这些垃圾必须是垃圾   稍后收集。

希望这会有所帮助!!