gtm (go tail mongo) is a utility written in Go which tails the MongoDB oplog and sends create, update, delete events to your code. It can be used to send emails to new users, index documents, write time series data, or something else.
- Go
- globalsign/mgo, a mongodb driver for Go
- mongodb
- Pass argument --master to mongod to ensure an oplog is created OR
- Setup replica sets to create oplog
go get github.com/rwynn/gtm
package main
import "github.com/globalsign/mgo"
import "github.com/globalsign/mgo/bson"
import "github.com/rwynn/gtm"
import "fmt"
func main() {
// get a mgo session
session, err := mgo.Dial("localhost")
if err != nil {
panic(err)
}
defer session.Close()
session.SetMode(mgo.Monotonic, true)
// nil options get initialized to gtm.DefaultOptions()
ctx := gtm.Start(session, nil)
// ctx.OpC is a channel to read ops from
// ctx.ErrC is a channel to read errors from
// ctx.Stop() stops all go routines started by gtm.Start
for {
// loop forever receiving events
select {
case err= <-ctx.ErrC:
// handle errors
fmt.Println(err)
case op:= <-ctx.OpC:
// op will be an insert, delete, update, or drop to mongo
// you can check which by calling
// op.IsInsert(), op.IsDelete(), op.IsUpdate(), or op.IsDrop()
// op.Data will get you the full document for inserts and updates
msg := fmt.Sprintf(`Got op <%v> for object <%v>
in database <%v>
and collection <%v>
and data <%v>
and timestamp <%v>`,
op.Operation, op.Id, op.GetDatabase(),
op.GetCollection(), op.Data, op.Timestamp)
fmt.Println(msg) // or do something more interesting
}
}
}
func NewUsers(op *gtm.Op) bool {
return op.Namespace == "users.users" && op.IsInsert()
}
// if you want to listen only for certain events on certain collections
// pass a filter function in options
ctx := gtm.Start(session, >m.Options{
NamespaceFilter: NewUsers, // only receive inserts in the user collection
})
// more options are available for tuning
ctx := gtm.Start(session, >m.Options{
NamespaceFilter nil, // op filter function that has access to type/ns ONLY
Filter nil, // op filter function that has access to type/ns/data
After: nil, // if nil defaults to LastOpTimestamp
OpLogDatabaseName: nil, // defaults to "local"
OpLogCollectionName: nil, // defaults to a collection prefixed "oplog."
CursorTimeout: nil, // defaults to 100s
ChannelSize: 0, // defaults to 20
BufferSize: 25, // defaults to 50. used to batch fetch documents on bursts of activity
BufferDuration: 0, // defaults to 750 ms. after this timeout the batch is force fetched
WorkerCount: 8, // defaults to 1. number of go routines batch fetching concurrently
Ordering: gtm.Document, // defaults to gtm.Oplog. ordering guarantee of events on the output channel
UpdateDataAsDelta: false, // set to true to only receive delta information in the Data field on updates (info straight from oplog)
DirectReadNs: []string{"db.users"}, // set to a slice of namespaces to read data directly from bypassing the oplog
DirectReadCursors: 10, // determines the requested number of cursors to parallelCollectionScan
Log: myLogger, // pass your own logger
})
If, in addition to tailing the oplog, you would like to also read entire collections you can set the DirectReadNs field to a slice of MongoDB namespaces. Documents from these collections will be read directly and output on the ctx.OpC channel.
You can wait till all the collections have been fully read by using the DirectReadWg wait group on the ctx.
go func() {
ctx.DirectReadWg.Wait()
fmt.Println("direct reads are done")
}()
gtm has support for sharded MongoDB clusters. You will want to start with a connection to the MongoDBconfig server to get the list of available shards.
// assuming the CONFIG server for a sharded cluster is running locally on port 27018
configSession, err = mgo.Dial("127.0.0.1:27018")
if err != nil {
panic(err)
}
// get the list of shard servers
shardInfos := gtm.GetShards(configSession)
for each shard you will create a session and append it to a slice of sessions
var shardSessions []*mgo.Session
// add each shard server to the sync list
for _, shardInfo := range shardInfos {
log.Printf("Adding shard found at %s\n", shardInfo.GetURL())
shardURL := shardInfo.GetURL()
shard, err := mgo.Dial(shardURL)
if err != nil {
panic(err)
}
shardSessions = append(shardSessions, shard)
}
finally you will want to start a multi context. The multi context behaves just like a single context except that it tails multiple shard servers and coalesces the events to a single output channel
multiCtx := gtm.StartMulti(shardSessions, nil)
after you have created the multi context for all the shards you can handle new shards being added to the cluster at some later time by adding a listener. You will want to add this listener before you enter a loop to read events from the multi context.
insertHandler := func(shardInfo *gtm.ShardInfo) (*mgo.Session, error) {
log.Printf("Adding shard found at %s\n", shardInfo.GetURL())
shardURL := shardInfo.GetURL()
return mgo.Dial(shardURL)
}
multiCtx.AddShardListener(configSession, nil, insertHandler)
If you'd like to unmarshall MongoDB documents into your own struct instead of the document getting unmarshalled to a generic map[string]interface{} you can use a custom unmarshal function:
type MyDoc struct {
Id interface{} "_id"
Foo string "foo"
}
func custom(namespace string, raw *bson.Raw) (interface{}, error) {
// use namespace, e.g. db.col, to map to a custom struct
if namespace == "test.test" {
var doc MyDoc
if err := raw.Unmarshal(&doc); err == nil {
return doc, nil
} else {
return nil, err
}
}
return nil, errors.New("unsupported namespace")
}
ctx := gtm.Start(session, >m.Options{
Unmarshal: custom,
}
for {
select {
case op:= <-ctx.OpC:
if op.Namespace == "test.test" {
doc := op.Doc.(MyDoc)
fmt.Println(doc.Foo)
}
}
}
You may want to distribute event handling between a set of worker processes on different machines. To do this you can leverage the github.com/rwynn/gtm/consistent package.
Create a TOML document containing a list of all the event handlers.
Workers = [ "Tom", "Dick", "Harry" ]
Create a consistent filter to distribute the work between Tom, Dick, and Harry. A consistent filter needs to acces the Data attribute of each op so it needs to be set as a Filter as opposed to a NamespaceFilter.
name := flag.String("name", "", "the name of this worker")
flag.Parse()
filter, filterErr := consistent.ConsistentHashFilterFromFile(*name, "/path/to/toml")
if filterErr != nil {
panic(filterErr)
}
// there is also a method **consistent.ConsistentHashFilterFromDocument** which allows
// you to pass a Mongo document representing the config if you would like to avoid
// copying the same config file to multiple servers
Pass the filter into the options when calling gtm.Tail
ctx := gtm.Start(session, >m.Options{Filter: filter})
If you have your multiple filters you can use the gtm utility method ChainOpFilters
func ChainOpFilters(filters ...OpFilter) OpFilter
Gtm will attempt to enable MongoDB's parallel collection scan feature for direct reads. Currently when using the WiredTiger storage engine this will be disabled since WiredTiger only returns 1 cursor. In the future, when WiredTiger is enhanced to support more than 1 cursor on a parallel collection scan, Gtm should enable and use multiple cursors without an upgrade.
So, currently to get a massive speed up on direct reads one needs to use the mmapv1 storage engine which unfortunately is not the default.
The number of cursors requested per collection is configurable via DirectReadCursors. The number of cursors actually returned by
MongoDB may be less than the requested amount.
For more information on see Parallel Collection Scan.