226 lines
8.8 KiB
TOML
226 lines
8.8 KiB
TOML
# Welcome to the InfluxDB configuration file.
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# If hostname (on the OS) doesn't return a name that can be resolved by the other
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# systems in the cluster, you'll have to set the hostname to an IP or something
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# that can be resolved here.
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# hostname = ""
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bind-address = "0.0.0.0"
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# Once every 24 hours InfluxDB will report anonymous data to m.influxdb.com
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# The data includes raft name (random 8 bytes), os, arch and version
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# We don't track ip addresses of servers reporting. This is only used
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# to track the number of instances running and the versions which
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# is very helpful for us.
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# Change this option to true to disable reporting.
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reporting-disabled = false
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[logging]
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# logging level can be one of "debug", "info", "warn" or "error"
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level = "info"
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file = "influxdb.log" # stdout to log to standard out
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# Configure the admin server
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[admin]
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port = 8083 # binding is disabled if the port isn't set
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assets = "./admin"
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# Configure the http api
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[api]
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port = 8086 # binding is disabled if the port isn't set
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# ssl-port = 8084 # Ssl support is enabled if you set a port and cert
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# ssl-cert = /path/to/cert.pem
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# connections will timeout after this amount of time. Ensures that clients that misbehave
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# and keep alive connections they don't use won't end up connection a million times.
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# However, if a request is taking longer than this to complete, could be a problem.
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read-timeout = "5s"
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[input_plugins]
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# Configure the graphite api
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[input_plugins.graphite]
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enabled = false
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# port = 2003
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# database = "" # store graphite data in this database
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# udp_enabled = true # enable udp interface on the same port as the tcp interface
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# Configure the udp api
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[input_plugins.udp]
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enabled = false
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# port = 4444
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# database = ""
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# Configure multiple udp apis each can write to separate db. Just
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# repeat the following section to enable multiple udp apis on
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# different ports.
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[[input_plugins.udp_servers]] # array of tables
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enabled = false
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# port = 5551
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# database = "db1"
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# Raft configuration
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[raft]
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# The raft port should be open between all servers in a cluster.
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# However, this port shouldn't be accessible from the internet.
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port = 8090
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# Where the raft logs are stored. The user running InfluxDB will need read/write access.
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dir = "/tmp/influxdb/development/raft"
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# election-timeout = "1s"
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[storage]
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dir = "/tmp/influxdb/development/db"
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# How many requests to potentially buffer in memory. If the buffer gets filled then writes
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# will still be logged and once the local storage has caught up (or compacted) the writes
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# will be replayed from the WAL
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write-buffer-size = 10000
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# the engine to use for new shards, old shards will continue to use the same engine
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default-engine = "leveldb"
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# The default setting on this is 0, which means unlimited. Set this to something if you want to
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# limit the max number of open files. max-open-files is per shard so this * that will be max.
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max-open-shards = 0
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# The default setting is 100. This option tells how many points will be fetched from LevelDb before
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# they get flushed into backend.
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point-batch-size = 100
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# The number of points to batch in memory before writing them to leveldb. Lowering this number will
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# reduce the memory usage, but will result in slower writes.
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write-batch-size = 5000000
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[storage.engines.leveldb]
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# Maximum mmap open files, this will affect the virtual memory used by
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# the process
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max-open-files = 1000
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# LRU cache size, LRU is used by leveldb to store contents of the
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# uncompressed sstables. You can use `m` or `g` prefix for megabytes
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# and gigabytes, respectively.
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lru-cache-size = "200m"
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[storage.engines.rocksdb]
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# Maximum mmap open files, this will affect the virtual memory used by
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# the process
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max-open-files = 40
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# LRU cache size, LRU is used by rocksdb to store contents of the
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# uncompressed sstables. You can use `m` or `g` prefix for megabytes
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# and gigabytes, respectively.
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lru-cache-size = "200m"
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[storage.engines.hyperleveldb]
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# Maximum mmap open files, this will affect the virtual memory used by
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# the process
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max-open-files = 40
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# LRU cache size, LRU is used by rocksdb to store contents of the
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# uncompressed sstables. You can use `m` or `g` prefix for megabytes
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# and gigabytes, respectively.
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lru-cache-size = "200m"
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[storage.engines.lmdb]
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map-size = "100g"
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[cluster]
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# A comma separated list of servers to seed
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# this server. this is only relevant when the
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# server is joining a new cluster. Otherwise
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# the server will use the list of known servers
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# prior to shutting down. Any server can be pointed to
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# as a seed. It will find the Raft leader automatically.
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# Here's an example. Note that the port on the host is the same as the raft port.
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# seed-servers = ["hosta:8090","hostb:8090"]
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# Replication happens over a TCP connection with a Protobuf protocol.
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# This port should be reachable between all servers in a cluster.
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# However, this port shouldn't be accessible from the internet.
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protobuf_port = 8099
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protobuf_timeout = "2s" # the write timeout on the protobuf conn any duration parseable by time.ParseDuration
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protobuf_heartbeat = "200ms" # the heartbeat interval between the servers. must be parseable by time.ParseDuration
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protobuf_min_backoff = "1s" # the minimum backoff after a failed heartbeat attempt
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protobuf_max_backoff = "10s" # the maxmimum backoff after a failed heartbeat attempt
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# How many write requests to potentially buffer in memory per server. If the buffer gets filled then writes
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# will still be logged and once the server has caught up (or come back online) the writes
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# will be replayed from the WAL
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write-buffer-size = 10000
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# the maximum number of responses to buffer from remote nodes, if the
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# expected number of responses exceed this number then querying will
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# happen sequentially and the buffer size will be limited to this
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# number
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max-response-buffer-size = 100
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# When queries get distributed out to shards, they go in parallel. This means that results can get buffered
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# in memory since results will come in any order, but have to be processed in the correct time order.
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# Setting this higher will give better performance, but you'll need more memory. Setting this to 1 will ensure
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# that you don't need to buffer in memory, but you won't get the best performance.
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concurrent-shard-query-limit = 10
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# These options specify how data is sharded across the cluster. There are two
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# shard configurations that have the same knobs: short term and long term.
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# Any series that begins with a capital letter like Exceptions will be written
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# into the long term storage. Any series beginning with a lower case letter
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# like exceptions will be written into short term. The idea being that you
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# can write high precision data into short term and drop it after a couple
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# of days. Meanwhile, continuous queries can run downsampling on the short term
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# data and write into the long term area.
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[sharding]
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# how many servers in the cluster should have a copy of each shard.
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# this will give you high availability and scalability on queries
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replication-factor = 1
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[sharding.short-term]
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# each shard will have this period of time. Note that it's best to have
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# group by time() intervals on all queries be < than this setting. If they are
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# then the aggregate is calculated locally. Otherwise, all that data gets sent
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# over the network when doing a query.
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duration = "7d"
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# split will determine how many shards to split each duration into. For example,
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# if we created a shard for 2014-02-10 and split was set to 2. Then two shards
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# would be created that have the data for 2014-02-10. By default, data will
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# be split into those two shards deterministically by hashing the (database, serise)
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# tuple. That means that data for a given series will be written to a single shard
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# making querying efficient. That can be overridden with the next option.
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split = 1
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# You can override the split behavior to have the data for series that match a
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# given regex be randomly distributed across the shards for a given interval.
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# You can use this if you have a hot spot for a given time series writing more
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# data than a single server can handle. Most people won't have to resort to this
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# option. Also note that using this option means that queries will have to send
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# all data over the network so they won't be as efficient.
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# split-random = "/^hf.*/"
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[sharding.long-term]
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duration = "30d"
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split = 1
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# split-random = "/^Hf.*/"
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[wal]
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dir = "/tmp/influxdb/development/wal"
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flush-after = 1000 # the number of writes after which wal will be flushed, 0 for flushing on every write
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bookmark-after = 1000 # the number of writes after which a bookmark will be created
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# the number of writes after which an index entry is created pointing
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# to the offset of the first request, default to 1k
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index-after = 1000
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# the number of requests per one log file, if new requests came in a
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# new log file will be created
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requests-per-logfile = 10000
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