buckytools

README

Go Buckytools

Tools for managing large consistent hashing Graphite clusters.

Buckminster (Bucky) Fuller once said,

If you want to teach people a new way of thinking, don’t bother trying to teach them. Instead, give them a tool, the use of which will lead to new ways of thinking.

Carbon molecules known as fullerenes were also named after Bucky due to their geodesic arrangement of atoms. So, this is my contribution to the Graphite naming scheme.

When working large consistent hashing Graphite clusters doing simple maintenance can involve a lot of data moving around. Normally, one would reach for the Carbonate tools:

https://github.com/jssjr/carbonate

These are good tools and I highly recommend them.

However, when the terabytes of WSP files and the number of storage nodes stack up you start to find scaling problems:

• The python implementation of whisper-fill is slow
• There is no atomic method to rebalance a single metric resulting in query inconsistency for possible days after the metric was moved
• Handling renames and resulting backfills at scale is still difficult

So I wanted to use the speed and concurrency of Go to build more efficient tools to help manage large consistent hashing cluster.

Tools

These are the tools included and their functionality.

• bucky-pickle-relay -- A daemon that accepts and decodes Graphite's Pickle protocol and will tcp stream the equivalent plaintext version to a carbon-relay. Useful with carbon-c-relay.
• bucky-fill -- A whisper-fill compatible utility that is nearly an order of magnitude faster.
• bucky-isempty -- A utility for discovering WSP databases that contain no valid data points.
• buckyd -- A daemon for each Graphite node that tracks the configuration of the hash ring and exposes a REST API for interacting with the raw metric DBs on disk.
• bucky -- Command line Graphite cluster manager. Modules:
  • backfill -- Backfill old metrics into new names.
  • delete -- Delete metrics via list or regular expression.
  • du -- Measure the storage consumed by a list of regular expression of metrics.
  • inconsistent -- Find metrics that are stored in the wrong server according to the hash ring.
  • json -- Convert newline separated lists to JSON arrays.
  • list -- Discover and verify metrics.
  • locate -- Calculate metric locations from the hash ring.
  • rebalance -- Move inconsistent metrics to the correct location and delete the source immediately after successful backfill.
  • restore -- Restore from a tar archive.
  • severs -- List each server's known hash ring and verify that all hash rings are consistent.
  • tar -- Make an archive of a list or regular expression of metric names and dump it in tar format to STDOUT.
• gentestmetrics -- Command that generates random Graphite style metrics to stdout purely for testing.
• bucky-sparsify -- Rewrites .wsp files into sparse files.

The heavy lifting commands use a set of worker threads to do IO work which can be set at the command line with -w.

Assumptions

These tools assume the following are true:

• You Graphite carbon-cache servers have one Whisper DB store. Not multiple mount points with carbon-cache configured with their own DB store.
• Your hash ring is set to a REPLICATION_FACTOR of 1

These aren't set in stone, just what I was working with as I built the tool. I very much hope that some of these will be solved with further development.

Daemon Usage

Each data storage node in the Graphite cluster needs a buckyd daemon running as the same user as the other Graphite tools. I use an Upstart job to keep mine running. The important bit here is that you must pass to the daemon as arguments the members of the consistent hash ring.

$ cat /etc/init/buckyd.conf
description "Buckyd Daemon for Managing Graphite Clusters"
author      "Jack Neely <jjneely@42lines.net>"

setuid graphite

exec /path/to/buckyd -node graphite010-g5 \
    -sparse -hash carbon -b 192.168.1.1:5678 \
graphite010-g5:a graphite010-g5:b \
graphite011-g5:a graphite011-g5:b \
graphite012-g5:a graphite012-g5:b

Here -node is the name of this Graphite node in the hashring (if different from what is derived from the host name). -b or -bind is the address to bind to. You can also specify -prefix`` where your Whisper data store is and -tmpdirwhere the daemon can write temporary files. The-sparseoption instructs buckyd to create sparse whisper files that take less disk space. The-hash` option chooses the hashring algorithm.

The non-option arguments are the servers and instances that make up the hashring. Order is important. The hashring members can be specified in the following formats:

• SERVER
• SERVER:INSTANCE
• SERVER:PORT:INSTANCE

This exposes a REST API that is documented in REST_API_NOTES.md.

Client Usage

The bucky tool is self documenting. You can run:

bucky help

to see a list of modules and available flags and what arguments are needed. Detailed help is available by specifying a module name:

bucky help backfill

Most commands need a --host or -h flag to specify the initial Graphite host to connect to where the client will discover the entire hash ring. You can also set the BUCKYHOST environment variable rather than specify this flag for each command.

Other common flags are:

• -s Operate only on the initial Graphite host.
• -f Requests the remote daemon to refresh its cache of local metrics.
• -j Read from STDIN or dump to STDOUT JSON data rather than text.
• -r Regular expression mode.
• -w Number of worker threads.

Examples

Rebalance a cluster with newly added storage nodes. Check if you need to use the -no-delete flag. The default behavior is to move metrics and delete the source after a successful copy.

$ bucky rebalance -h graphite010-g5:4242 \
    -w 25 2>&1 | tee rebalance.log

Discover the exact storage used by a set of metrics:

$ export BUCKYHOST=-h graphite010-g5:4242
$ bucky du -r '^1min\.ipvs\.'

Make a backup of all of the metrics in the carbon namespace. Using the pigz parallel gzip compression tool. (Normal gzip would otherwise bottleneck the process.)

$ bucky tar -w 25 -r '^carbon\.' | pigz > filename.tar

Backfill or rename metrics with a JSON hash of old name to new name. This does not delete the source metric. It is a copy/fill operation.

$ bucky backfill -w 25 foo.json

Find inconsistent metrics or metrics that are in the wrong place in the cluster according to the hashring:

$ bucky inconsistent

Building from Source

To build from the Go source:

• Make sure your GOPATH environment variable is set to your Go workspace.
• Run: go get github.com/jjneely/buckytools
• Change directory into $GOPATH/src/github.com/jjneely/buckytools
• Run: go install ./...
• Binaries should now be installed to $GOPATH/bin

This can also be built as a Debian/Ubuntu package. (Tested on Ubuntu Trusty, and Xenial.) The git-buildpackage is what I use to produce builds. This requires golang debian packages.

• Run: gbp buildpackage

Notes

Deleting Metrics

The daemon makes no effort to remove possibly empty directories when deleting a metric. This can potentially cause race conditions with carbon-cache.py creating a new metric in a would be deleted directory. Once carbon-cache.py closes the file handle to a file in a deleted directory that file will also be deleted. The delete action must not cause harm to other metrics.

To prune old or empty directories from your Graphite whisper store use a cron job similar to this:

/usr/bin/find ${prefix}/storage/whisper -type d -empty -mtime +1 -delete

This checks that the directory has not been modified in more than 1 day which, in most cases, avoids race conditions.

Google Snappy Compression

To further scale the speed at which this tool will move metric data from one location to another it uses Snappy compression by default. This can be disabled with the -no-encoding flag. When using many workers this can double (or more) the throughput. The Snappy compression frame protocol also handles CRC checks for data integrity.

To Do / Bugs / Contributing

Contributions are welcome! Please make a GitHub pull request. Below are some low hanging fruit (and some more annoying issues) that need help.

• Unit tests with Go's net/http/httptest package. Test that the buckyd daemon manipulates the on disk Whisper files correctly.

• Authentication -- Negotiate and Kerberos support. Probably Basic as well.

• Make all modules aware of possible duplicate metrics.

• Retries

• Graceful restarts and shutdowns? https://github.com/facebookgo/grace

• graphite-project/carbon's master branch contains this change:

  https://github.com/graphite-project/carbon/commit/024f9e67ca47619438951c59154c0dec0b

  This will cause a few metrics to be assigned a different position in the hash ring. We need to account for this algorithm change somehow.

  Buckytools supports multiple different hashing algorithms and this can be setup as a different support hashing type.

Documentation

Index

• Constants
• Variables
• func FindValidDataPoints(wsp *whisper.Whisper) ([]*whisper.TimeSeriesPoint, int, error)
• type JSONRingType
  • func (j *JSONRingType) String() string

Constants

const (
	// Buckytools suite version
	Version = "0.3.0"
)

Variables

var SupportedHashTypes = []string{
	"carbon",
	"jump_fnv1a",
}

SupportedHashTypes is the string identifiers of the hashing algorithms used for the consistent hash ring. This slice must be sorted.

Functions

func FindValidDataPoints

func FindValidDataPoints(wsp *whisper.Whisper) ([]*whisper.TimeSeriesPoint, int, error)

FindValidDataPoints does a backwards walk through time to examine the highest resolution data for each archive / time period. We collect valid data points and return them in a *[]TimeSeriesPoint. The second value return is an int containing the total number of points examined. This allows one to calculate the percentage of used and unused points stored in the Whisper database.

Types

type JSONRingType

type JSONRingType struct {
	Name     string
	Nodes    []string
	Algo     string
	Replicas int
}

JSONRingType is a datastructure that identifies the name of the server buckdy is running on and contains a slice of nodes which are "server:instance" (where ":instance" is optional) formatted strings

func (*JSONRingType) String

func (j *JSONRingType) String() string