- Command Line Options
- Version History
- Protocol
- Metrics
- Serialisation
- Testing
- Build
- Clients
- Acknowledgements
A TCP service for routing all requests to MongoDB via a centralised service. A few common features made available by this service are:
- All documents are versioned in a version history collection.
- All operations are timed and the metrics stored in a metrics collection.
Note: A C++17 compiler with coroutines-ts, or a C++20 compiler with coroutines support is required to build this project.
The service can be configured via the following command line options:
port
- Specify the port the service is to bind to via the-p
or--port
option. Default is2020
.threads
- The number of Boost ASIO IO Context threads to use via the-n
or--threads
option. Default is the value returned bystd::thread::hardware_concurrency
.mongoUri
- The full MongoDB connection uri to use. This should include the user credentials as well. Specify via the-m
or--mongo-uri
option. Mandatory option to start the service.versionHistoryDatabase
- The data to use to store version history documents. Specify via the-d
or--version-history-database
option. DefaultversionHistory
.versionHistoryCollection
- The collection to store version history documents in. Specify via the-c
or--version-history-collection
option. Defaultentities
.metricsDatabase
- The database in which to store request processing metrics to. Specify via the-s
or--metric-database
option. DefaultversionHistory
.metricsCollection
- The collection in which to store the metric documents. Specify via the-t
or--metric-collection
option. Defaultmetrics
.metricBatchSize
- The number of metrics to accumulate before saving to the desired store. Specify via the-w
or--metric-batch-size
option. Default100
.ilpServer
- The host name for the time series database that supports the ILP. Specify via the-i
or--ilp-server
option.ilpPort
- The port for the time series database that supports the ILP. Specify via the-x
or--ilp-port
option.ilpMeasurement
- The series/measurement name for metrics. Specify via the-y
or--ilp-series-name
option. Defaultmetrics
.logLevel
- The logging level for the service. Specify via-l
or--log-level
option. Defaultinfo
. Allowed values -debug, info, warn, critical
.logAsync
- Use asynchronous logger for the service (non-guaranteed and may lose some logs). Specify via-z
or--log-async
option. Defaulttrue
. Allowed values -true, false
.console
- Whether log messages are to be echoed to theconsole
as well. Specifytrue
via the-c
or--console
option. Defaultfalse
.dir
- Specify the output directory under which log files are to be stored via the-o
or--dir
option. Note that a trailing slash/
is mandatory. Defaultlogs/
.
All documents stored in the database will automatically be versioned on save. Deleting a document will move the current document into the version history database collection. This makes it possible to retrieve previous versions of a document as needed, as well as restore a document (regardless of whether it has been deleted or not).
All interactions are via BSON documents sent to the service. Each request must conform to the following document model:
action (string)
- The type of database action being performed. One ofcreate|retrieve|update|delete|count|index|dropCollection|dropIndex|bulk|pipeline|transaction|renameCollection
.database (string)
- The Mongo database the action is to be performed against.- Not needed for
transaction
action.
- Not needed for
collection (string)
- The Mongo collection the action is to be performed against.- Not needed for
transaction
action.
- Not needed for
document (document)
- The document payload to associate with the database operation. Forcreate
andupdate
this is assumed to be the documet that is being saved. Forretrieve
orcount
this is the query to execute. Fordelete
this is a simpledocument
with an_id
field.options (document)
- The options to associate with the Mongo request. These correspond to the appropriate options as used by the Mongo driver.metadata (document)
- Optional metadata to attach to the version history document that is created (not relevant forretrieve
obviously). This typically will include information about the user performing the action, any other information as relevant in the system that uses this service.application
- Optional name of the application accessing the service. Helps to retrieve database metrics for a specific application.correlationId (string)
- Optional correlation id to associate with the metric record created by this action. This is useful for tracing logs originating from a single operation/request within the overall system. This value is stored as a string value in the metric document to allow for sensible data types to used as the correlation id.skipVersion (bool)
- Optionalbool
value to indicate not to create a version history document for thisaction
. Useful when creating non-critical data such as logs.skipMetric (bool)
- Optionalbool
value to indicate not to create a metric document for thisaction
. Useful when calls are made a part of a monitoring framework, and volume of metrics generated overwhelms storage requirements.
The document payload contains all the information necessary to execute the
specified action
in the request.
The document
as specified will be inserted into the specified database
and
collection
. The BSON ObjectId property/field (_id
) must be included in
the document. The _id
is needed within the version history document associated
with the create action. If using unacknowledged writes, the auto-generated
_id
is not available, and hence we would need to create a new insert document
with the _id
set within the service. This involves a wasteful copy of data,
and hence we enforce the requirement on client specified _id
value.
Sample request payload:
{
"action": "create",
"database": "<database name>",
"collection": "<collection name>",
"document": {
"_id": {
"$oid": "5f35e5e1e799c52186039122"
},
"intValue": 123,
"floatValue": 123.0,
"boolValue": true,
"stringValue": "abc123",
"nested": {"key": "value"}
}
}
Sample response payload when version history document is created (default option):
{
"_id": {
"$oid": "5f35e5e19e48c37186539141"
},
"database": "versionHistory",
"collection": "entities",
"entity": {
"$oid": "5f35e5e1e799c52186039122"
}
}
Note: The _id
in the response is the object id of the version history
document that was created.
Sample response payload when version history document is not created:
{
"_id": {
"$oid": "5f35e5e19e48c37186539141"
},
"skipVersion": true
}
Note: The _id
in the response is the object id for the document as specified
in the input payload.
Retrieve obviously does not have any interaction with the version history system (unless you are retrieving versions). We provide this since one of the other purposes behind this service is to route/proxy all datastore interactions via this service.
Sample retrieve payload:
{
"action": "retrieve",
"database": "itest",
"collection": "test",
"document": {
"_id": {
"$oid": "5f35e6d8c7e3a976365b3751"
}
}
}
Sample response:
{
"result": {
"_id": {
"$oid": "5f35e5e1e799c52186039122"
},
"intValue": 123,
"floatValue": 123.0,
"boolValue": true,
"stringValue": "abc123",
"nested": {"key": "value"}
}
}
Count the number of documents matching the specified query document. The query document can be empty to get the count of all documents in the specified collection.
Sample count payload:
{
"action": "count",
"database": "itest",
"collection": "test",
"document": {}
}
Sample response:
{ "count" : 11350 }
Update is the most complex scenario. The service supports the two main update modes supported by Mongo:
- update - The data specified in the
document
sub-document is merged into the existing document(s). - replace - The data specified in the
document
is used to replace an existing document.
Updates are possible either by an explicit _id
field in the input document
,
or via a filter
sub-document that expresses the query used to identify the
candidate document(s) to update.
If both _id
and filter
are omitted an error document is returned.
The returned BSON document depends on whether a single-document or multi-document update request was made:
- Single-Document - For single document updates the full updated stored document
(
document
) and basic information about the associated version history document (history
) are returned. - Multi-Document - For multi-document updates, an array of BSON object ids for
successful updates (
success
), failed updates (failure
), and the basic information about the version history documents (history
).
The simple and direct update use case. If the document
has an _id
property,
the remaining properties are merged into the stored document. A version history
document with the resulting stored document is also created.
Sample update request by _id
:
{
"action": "update",
"database": "itest",
"collection": "test",
"document": {
"key1": "value1",
"_id": {
"$oid": "5f35e887bb516401e02b4701"
}
}
}
Sample response:
{
"document": {
"_id": {
"$oid": "5f35e887bb516401e02b4701"
},
"key": "value",
"key1": "value1"
},
"history": {
"_id": {
"$oid": "5f35e887e799c5218603915b"
},
"database": "itest",
"collection": "test",
"entity": {
"$oid": "5f35e887bb516401e02b4701"
}
}
}
Sample request payload:
{
"action": "update",
"database": "itest",
"collection": "test",
"skipVersion": true,
"document": {
"key1": "value1",
"_id": {
"$oid": "5f35e932d3698352cb3bd2d1"
}
}
}
In this case, only a placeholder response is returned as follows:
{ "skipVersion" : true }
If the document
has a replace
sub-document, then the existing document as
specified by the filter
query will be replaced. MongoDB will return as error
if an attempt is made to replace multiple documents (the query filter must return
a single document). A version history document is created with the replaced
document.
The following sample shows an example of performing a replace
action.
{
"action": "update",
"database": "itest",
"collection": "test",
"document": {
"filter": {
"_id": { "$oid": "5f3bc9e2502422053e08f9f1" }
},
"replace": {
"_id": { "$oid": "5f3bc9e2502422053e08f9f1" },
"key": "value",
"key1": "value1"
}
},
"options": { "upsert": true },
"application": "version-history-api",
"metadata": {
"revertedFrom": { "$oid": "5f3bc9e29ba4f45f810edf29" }
}
}
If the document
has a update
sub-document, then existing document(s) are
updated with the information contained in it. This is a merge operation where
only the fields specified in the update
are set on the candidate document(s).
A version history document is created for each updated document.
If the input filter
sub-document has an _id
property, and is of type BSON
Object Id, then a single document update is made.
As a simplification, it is possible to omit the $set
operator, if used in conjunction with a $unset
operator. All
top level properties other than _id
and $unset
are implicitly added to a $set
document in the actual update document
sent to MongoDB.
Sample request payload with explicit $set
:
{
"action": "update",
"database": "itest",
"collection": "test",
"document": {
"filter": {
"_id": {"$oid": "6435a62316d2310e800e4bf2"}
},
"update": {
"$unset": {"obsoleteProperty": 1},
"$set": {
"metadata.modified": {"$date": 1681237539583},
"metadata.user._id": {"$oid": "5f70ee572fc09200086c8f24"},
"metadata.user.username": "mqtt"
}
}
}
}
Sample request payload without $set
:
{
"action": "update",
"database": "itest",
"collection": "test",
"document": {
"filter": {
"_id": {"$oid": "6435a62316d2310e800e4bf2"}
},
"update": {
"$unset": {"obsoleteProperty": 1},
"metadata.modified": {"$date": 1681237539583},
"metadata.user._id": {"$oid": "5f70ee572fc09200086c8f24"},
"metadata.user.username": "user"
}
}
}
The document
represents the query to execute to find the candidate documents
to delete from the database
:collection
. The query is executed to retrieve
the candidate documents, and the documents removed from the specified
database:collection
. The retrieved documents are then written to the version
history database.
Sample delete request:
{
"action": "delete",
"database": "itest",
"collection": "test",
"document": {
"_id": { "$oid": "5f35ea61aa4ef01184492d71" }
}
}
Sample delete response:
{
"success": [{
"$oid": "5f35ea61aa4ef01184492d71"
}],
"failure": [],
"history": [{
"_id": {
"$oid": "5f35ea61e799c521860391a9"
},
"database": "versionHistory",
"collection": "entities",
"entity": {
"$oid": "5f35ea61aa4ef01184492d71"
}
}]
}
Drop the specified collection and all its containing documents. Specify an
empty document
in the payload to satisfy payload requirements. If you wish
to also remove all version history documents for the dropped collection, specify
clearVersionHistory
true
in the document
(revision history documents
will be removed asynchronously). Specify the write concern settings in the
optional options
sub-document.
Sample drop payload specifying removal of all associated revision history documents:
{
"action": "dropCollection",
"database": "itest",
"collection": "test",
"document": {"clearVersionHistory": true}
}
Sample response:
{ "dropCollection" : true }
The document
represents the specification for the index to be created.
Additional options for the index (such as unique) can be specified via the
optional options
sub-document.
The document
represents the index specification for the
dropIndexes
command. Additional options for the index (such as write concern) can be specified
via the optional options
sub-document.
One of the following properties must be specified in the document
:
name
- Thename
of the index to drop. Should be astring
value.specification
- The full document specification of the index that was created.
Bulk insert/delete documents. Corresponding version history documents for
inserted and/or deleted documents are created unless skipVersion
is specified.
The documents to insert or delete in bulk must be specified as
BSON array properties in the document
part of the payload. Multiple arrays
may be specified as appropriate.
insert
- Array of documents which are to be inserted. All documents must have a BSON ObjectId_id
property.delete
- Array of document specifications which represent the deletes. Deletes are slow since the query specifications are used to retrieve the documents being deleted and create the corresponding version history documents. Retrieving the documents in a loop adds significant processing time. For example the bulk delete test (deleting 10000 documents) takes about 15 seconds to run.
Sample bulk create payload:
{
"action": "bulk",
"database": "itest",
"collection": "test",
"document": {
"insert": [{
"_id": {
"$oid": "5f6ba5f9de326c57bd64efb1"
},
"key": "value1"
},
{
"_id": {
"$oid": "5f6ba5f9de326c57bd64efb2"
},
"key": "value2"
}],
"delete": [{
"_id": {
"$oid": "5f6ba5f9de326c57bd64efb1"
}
}]
}
}
Sample response for the above payload:
{ "create" : 2, "history": 3, "delete" : 1 }
Basic support for using aggregation pipeline features. This feature will be expanded as use cases expand over a period of time.
The document
in the payload must include a specification
array of
documents which correspond to the match
, lookup
...
specifications for the aggregation pipeline operation (stage). The matching documents
will be returned in a results
array in the response.
The following operators are supported:
$match
$lookup
$unwind
$group
$sort
$limit
$project
$addFields
$facet
$search
- Note requirement forsearch
to be the first stage in a pipeline.$unionWith
Sample request payload:
{
"action": "pipeline",
"database": "itest",
"collection": "test",
"document": {
"specification": [
{"$match": {"_id": {"$oid": "5f861c8452c8ca000d60b783"}}},
{"$sort": {"_id": -1 }},
{"$limit": 20},
{"$lookup": {
"localField": "user._id",
"from": "user",
"foreignField": "_id",
"as": "users"
}},
{"$lookup": {
"localField": "group._id",
"from": "group",
"foreignField": "_id",
"as": "groups"
}}
]
}
}
Execute a sequence of actions in a transaction. Nest the individual actions
that are to be performed in the transaction within the document
sub-document.
The document
in the payload must include an items
array of documents.
Each document in the array represents the full specification for the action in
the transaction. The document specification is the same as the
document specification for using the service.
The specification for the action document in the items
array is:
action (string)
- The type of action to perform. Should be one ofcreate|update|delete
.database (string)
- The database in which the step is to be performed.collection (string)
- The collection in which the step is to be performed.document (document)
- The BSON specification for executing theaction
.skipVersion (bool)
- Do not create version history document for this action.
The response to a transaction request has the following structure:
created (int)
- The number of documents that were created in this transaction.updated (int)
- The number of documents that were updated in this transaction.deleted (int)
- The number of documents that were deleted in this transaction.history (document)
- Metadata about version history documents that were created.database (string)
- The database used to store version history data.collection (string)
- The collection used to store version history data.created (array<oid>)
- History document object ids for new documents created in the transaction.updated (array<oid>)
- History document object ids for documents updated in the transaction.deleted (array<oid>)
- History document object ids for documents deleted in the transaction.
See samples for sample request/response payloads from the integration test suite.
Update at present in only partially supported. Strong assumption is made that
the document being updated is a full replacement. In other words, there is a
strong assumption that the document includes the _id
property, and that the
intention is to replace the existing document.
Rename a collection
in the specified database
. If a collection
already exists with the
document.target
name, an error is returned. The option to automatically drop a pre-existing
collection as supported by MongoDB is not supported. For such cases, use the dropCollection
action prior to invoking this action. Specify the write concern settings in the
optional options
sub-document.
This is a potentially heavy-weight operation. All version history documents for the specified database::collection combination are also updated. Version history document update is performed asynchronously. The operation enqueues an update operation to the version history documents, and returns. This can lead to queries against version history returning stale information for a short period of time.
Note: Renaming the collection in all associated version history documents may be the wrong choice.
In chronological terms, those documents were associated with the previous collection
. Only future revisions
are associated with the renamed target
. However, this can create issues in terms of retrieval, or if
iterating over records for some other purpose, or if a new collection with the previous name is created
in future.
Sample rename payload:
{
"action": "renameCollection",
"database": "itest",
"collection": "test",
"document": {"target": "test-renamed"}
}
Sample response payload:
{
"database": "itest",
"collection": "test-renamed"
}
Create, update and delete actions only return some meta information about the action that was performed. The assumption is that caller already has all the document information needed, and there is no need for the service to return that information.
The retrieve
action of course returns the results of executing the database
query encapsulated in the document
property of the request payload. The
following document model is returned as the response:
error
- Astring
value in case an error was encountered as a result of executing the query. Caller should always check for existence of this property.result
- A BSON document that is returned if the query included an_id
property. In such a case it is assumed that the query is a lookup for a single document.results
- A BSON array with document(s) that were retrieved from the database for the query.
See transaction for sample request/response payloads for transaction requests.
Options specified in the request payload are parsed into the appropriate
option
document for the specified action
.
At present only documents with BSON ObjectId _id
is supported.
Metrics are collected for all requests to the service (unless client specifies skipMetric
). Metrics may be
stored in MongoDB itself, or a service that supports the ILP.
Metrics are collected in the specified database
and collection
combination
(or their defaults). No TTL index is set on this (as it is left to the user's
requirements). A date
property is stored to create a TTL index as required.
The schema for a metric is as follows:
{
"_id": ObjectId("5fd4b7e55f1ba96a695d1446"),
"action": "retrieve",
"database": "wpreading2",
"collection": "databaseVersion",
"size": 88,
"time": 414306,
"timestamp": 437909021088978,
"date": Date(437909021),
"application": "bootstrap"
}
- action - The database action performed by the client.
- database - The database against which the action was performed.
- collection - The collection against which the action was performed.
- size - The total size of the response document.
- time - The time in
nanoseconds
for the action (includes any interaction with version history). - timestamp - The time since UNIX epoch in
nanoseconds
for use when exporting to other timeseries databases. - date - The BSON date at which the metric was created. Use to define a TTL index as appropriate.
- application - The application that invoked the service if specified in the request payload.
Metrics may be stored in a time series database of choice that supports the ILP. We have only tested
storing metrics in QuestDB. All the fields (except the _id
) are stored in
the TSDB. The duration
, and size
values are stored as field sets and the other values stored as tag sets.
The name for the series (measurement) can be specified via the command line argument, or will default to
the name of the metrics
collection.
A simple serialisation framework is also provided. Uses the visit_struct library to automatically serialise and deserialise visitable classes/structs.
A simple serialisation framework to serialise and deserialise visitable classes/structs to and from BSON. See the test suite for sample use of the framework.
The framework provides the following primary functions to handle (de)serialisation:
marshall<Model>( const Type& )
- to marshall the specified object to a BSON document.unmarshall<Model>( bsoncxx::document::view view )
- unmarshall the BSON document into a default constructed object.unmarshall<Model>( Model& m, bsoncxx::document::view view )
- unmarshall the BSON document into the specified model instance.
The framework handles non-visitable members within a visitable root object. Custom implementations can be implemented.
- For non-visitable classes/structs, implement the following functions as appropriate:
bsoncxx::types::bson_value::value bson( const <Class/Struct Type>& model )
that will produce a BSON document as a value variant for the data encapsulated in the object.void set( <Class/Struct Type>& field, bsoncxx::types::bson_value::view value )
that will populate the model instance from the BSON value variant.
- For partially visitable classes/structs, implement the following
populate
callback functions as appropriate:void populate( const <Class/Struct Type>& model, bsoncxx::builder::stream::document& doc )
to add the non-visitable fields to the BSON stream builder.void populate( <Class/Struct Type>& model, bsoncxx::document::view view )
to populate the non-visitable fields in the object from the BSON document.
A simple serialisation framework to serialise and deserialise visitable classes/structs to and from JSON. See the test suite for sample use of the framework.
Similar to the BSON framework, the JSON framework also handles non-visitable members within a visitable root object. Custom implementations can be implemented.
- For non-visitable classes/structs, implement the following functions as appropriate:
boost::json::value json( const <Class/Struct Type>& model )
that will produce a JSON value for the data encapsulated in the object.void set( const char* name, <Class/Struct Type>& field, simdjson::ondemand::value& value )
that will populate the model instance from the JSON value.
- For partially visitable classes/structs, implement the following
populate
callback functions as appropriate:void populate( const <Class/Struct Type>& model, boost::json::object& object )
to add non-visitable fields to the JSON object.void populate( const <Class/Struct Type>& model, simdjson::ondemand::object& object )
to populate non-visitable fields from the JSON object.
JSON input mostly comes via HTTP from untrusted sources. Consequently, there is a need for validating the JSON
input. Basic support for input validation is provided via a validate
function.
A validate( const char*, M& )
function is defined. This is to for validating the JSON input being parsed. A
default specialisation is provided for std::string
fields. This rejects strings with more than 40%
(configurable)
special characters. Users are advised to implement specific implementations specific to their domain requirements.
Users may also use environment variables to influence the default implementation.
JSON_PARSE_VALIDATION_IGNORE
- Environment variable that expects a comma or space separated list of field names that should be ignored by the validator. Default values arepassword, version
. Example:export SPT_JSON_PARSE_VALIDATION_IGNORE='password, file, version, firmware, identifier'
SPT_JSON_PARSE_VALIDATION_RATIO
- Environment variable (double
) that sets the maximum allowed ratio of special characters in the input string. Default is0.4
. Example:export SPT_JSON_PARSE_VALIDATION_RATIO='0.35'
Integration tests for the service will be developed in a few different languages
to ensure full interoperability. The test suites will be available under the
test
directory or under the client
directory. The following suites are present at present:
C++
- Integration - Integration test suite under the
test/integration
directory. - Performance - Performance test suite under the
test/performance
directory.
- Integration - Integration test suite under the
Python
- See features for the test suite.Julia
- See test for the test suite.go
- Simple test program under thetest/go
directory.(cd mongo-service/test/go; go build -o /tmp/gomongo; /tmp/gomongo)
A simple connection pool implementation is provided in the api, along with its associated test suite. The implementation is based on a factory function that can create valid connections as needed.
The pool is managed using a std::deque
. Connections returned to the pool are
added to the back (least idle), while acquiring a connection pops it from the
front (most idle) of the deque
.
Configuration is via a simple structure for common options such as initial size,
max pool size, max connection size, and maximum idle time for a connection. It
supports a simple validity check (via a mandatory bool valid()
function)
of the connection before adding it back to the pool.
A maxIdleTime
property is used to close connections that have been idling more
than the specified time. The initialSize
property is also used as a minimum
pool size configuration. The minimum size is always maintained regardless of
idle time.
Acquiring a connection from the pool returns a std::optional<Proxy>
instance.
If the maximum number of connections has been reached, std::nullopt
is returned.
The Proxy implements RAII by returning the connection to the pool when the
instance is destroyed.
A wrapper is used to associate a last used timestamp to the connection. This is used to enforce maximum idle time policy on the underlying connection.
A sample async client using coroutines with connection pool implementation is available under the client directory.
The performance test suite performs a simple CRUD operation using the service. Each test creates a document, retrieves the document, updates the document and finally deletes the document. All operations other than retrieve will create an associated version history document in the database. All operations also create a corresponding metric document in the database. Thus a CRUD operation involves approximately 12 database operations internally.
The tests are set up to run each set of CRUD operations 10
times (iterations),
and a run is repeated a second time to get better average and variability numbers.
Separate runs are set up with 10, 50, 100, 500
and 1000
concurrent threads.
All tests are against the simple docker stack
running on the same machine. A key goal of the test is to ensure that there are
no errors while running the test.
The following numbers as recorded on my laptop during normal use (plenty of other applications and processes running) and with the Docker daemon restricted to using half the available CPU cores.
[==========] Running 5 benchmarks.
[ RUN ] SocketClientFixture.crud(int concurrency = 10) (2 runs, 10 iterations per run)
[ DONE ] SocketClientFixture.crud(int concurrency = 10) (1356.777305 ms)
[ RUNS ] Average time: 678388.652 us (~303172.494 us)
Fastest time: 464013.326 us (-214375.326 us / -31.601 %)
Slowest time: 892763.979 us (+214375.327 us / +31.601 %)
Median time: 678388.652 us (1st quartile: 464013.326 us | 3rd quartile: 892763.979 us)
Average performance: 1.47408 runs/s
Best performance: 2.15511 runs/s (+0.68103 runs/s / +46.20025 %)
Worst performance: 1.12012 runs/s (-0.35396 runs/s / -24.01254 %)
Median performance: 1.47408 runs/s (1st quartile: 2.15511 | 3rd quartile: 1.12012)
[ITERATIONS] Average time: 67838.865 us (~30317.249 us)
Fastest time: 46401.333 us (-21437.533 us / -31.601 %)
Slowest time: 89276.398 us (+21437.533 us / +31.601 %)
Median time: 67838.865 us (1st quartile: 46401.333 us | 3rd quartile: 89276.398 us)
Average performance: 14.74081 iterations/s
Best performance: 21.55111 iterations/s (+6.81029 iterations/s / +46.20025 %)
Worst performance: 11.20117 iterations/s (-3.53964 iterations/s / -24.01254 %)
Median performance: 14.74081 iterations/s (1st quartile: 21.55111 | 3rd quartile: 11.20117)
[ RUN ] SocketClientFixture.crud(int concurrency = 50) (2 runs, 10 iterations per run)
[ DONE ] SocketClientFixture.crud(int concurrency = 50) (3786.378171 ms)
[ RUNS ] Average time: 1893189.086 us (~131220.814 us)
Fastest time: 1800401.958 us (-92787.127 us / -4.901 %)
Slowest time: 1985976.213 us (+92787.127 us / +4.901 %)
Median time: 1893189.086 us (1st quartile: 1800401.958 us | 3rd quartile: 1985976.213 us)
Average performance: 0.52821 runs/s
Best performance: 0.55543 runs/s (+0.02722 runs/s / +5.15369 %)
Worst performance: 0.50353 runs/s (-0.02468 runs/s / -4.67212 %)
Median performance: 0.52821 runs/s (1st quartile: 0.55543 | 3rd quartile: 0.50353)
[ITERATIONS] Average time: 189318.909 us (~13122.081 us)
Fastest time: 180040.196 us (-9278.713 us / -4.901 %)
Slowest time: 198597.621 us (+9278.713 us / +4.901 %)
Median time: 189318.909 us (1st quartile: 180040.196 us | 3rd quartile: 198597.621 us)
Average performance: 5.28209 iterations/s
Best performance: 5.55432 iterations/s (+0.27222 iterations/s / +5.15369 %)
Worst performance: 5.03531 iterations/s (-0.24679 iterations/s / -4.67212 %)
Median performance: 5.28209 iterations/s (1st quartile: 5.55432 | 3rd quartile: 5.03531)
[ RUN ] SocketClientFixture.crud(int concurrency = 100) (2 runs, 10 iterations per run)
[ DONE ] SocketClientFixture.crud(int concurrency = 100) (6902.353423 ms)
[ RUNS ] Average time: 3451176.712 us (~85190.281 us)
Fastest time: 3390938.086 us (-60238.626 us / -1.745 %)
Slowest time: 3511415.337 us (+60238.625 us / +1.745 %)
Median time: 3451176.712 us (1st quartile: 3390938.086 us | 3rd quartile: 3511415.337 us)
Average performance: 0.28976 runs/s
Best performance: 0.29490 runs/s (+0.00515 runs/s / +1.77646 %)
Worst performance: 0.28479 runs/s (-0.00497 runs/s / -1.71551 %)
Median performance: 0.28976 runs/s (1st quartile: 0.29490 | 3rd quartile: 0.28479)
[ITERATIONS] Average time: 345117.671 us (~8519.028 us)
Fastest time: 339093.809 us (-6023.863 us / -1.745 %)
Slowest time: 351141.534 us (+6023.863 us / +1.745 %)
Median time: 345117.671 us (1st quartile: 339093.809 us | 3rd quartile: 351141.534 us)
Average performance: 2.89756 iterations/s
Best performance: 2.94904 iterations/s (+0.05147 iterations/s / +1.77646 %)
Worst performance: 2.84785 iterations/s (-0.04971 iterations/s / -1.71551 %)
Median performance: 2.89756 iterations/s (1st quartile: 2.94904 | 3rd quartile: 2.84785)
[ RUN ] SocketClientFixture.crud(int concurrency = 500) (2 runs, 10 iterations per run)
[ DONE ] SocketClientFixture.crud(int concurrency = 500) (37825.690178 ms)
[ RUNS ] Average time: 18912845.089 us (~77556.025 us)
Fastest time: 18858004.698 us (-54840.391 us / -0.290 %)
Slowest time: 18967685.480 us (+54840.391 us / +0.290 %)
Median time: 18912845.089 us (1st quartile: 18858004.698 us | 3rd quartile: 18967685.480 us)
Average performance: 0.05287 runs/s
Best performance: 0.05303 runs/s (+0.00015 runs/s / +0.29081 %)
Worst performance: 0.05272 runs/s (-0.00015 runs/s / -0.28913 %)
Median performance: 0.05287 runs/s (1st quartile: 0.05303 | 3rd quartile: 0.05272)
[ITERATIONS] Average time: 1891284.509 us (~7755.602 us)
Fastest time: 1885800.470 us (-5484.039 us / -0.290 %)
Slowest time: 1896768.548 us (+5484.039 us / +0.290 %)
Median time: 1891284.509 us (1st quartile: 1885800.470 us | 3rd quartile: 1896768.548 us)
Average performance: 0.52874 iterations/s
Best performance: 0.53028 iterations/s (+0.00154 iterations/s / +0.29081 %)
Worst performance: 0.52721 iterations/s (-0.00153 iterations/s / -0.28913 %)
Median performance: 0.52874 iterations/s (1st quartile: 0.53028 | 3rd quartile: 0.52721)
[ RUN ] SocketClientFixture.crud(int concurrency = 1000) (2 runs, 10 iterations per run)
[ DONE ] SocketClientFixture.crud(int concurrency = 1000) (70436.871301 ms)
[ RUNS ] Average time: 35218435.650 us (~1036096.530 us)
Fastest time: 34485804.768 us (-732630.883 us / -2.080 %)
Slowest time: 35951066.533 us (+732630.883 us / +2.080 %)
Median time: 35218435.650 us (1st quartile: 34485804.768 us | 3rd quartile: 35951066.533 us)
Average performance: 0.02839 runs/s
Best performance: 0.02900 runs/s (+0.00060 runs/s / +2.12444 %)
Worst performance: 0.02782 runs/s (-0.00058 runs/s / -2.03786 %)
Median performance: 0.02839 runs/s (1st quartile: 0.02900 | 3rd quartile: 0.02782)
[ITERATIONS] Average time: 3521843.565 us (~103609.653 us)
Fastest time: 3448580.477 us (-73263.088 us / -2.080 %)
Slowest time: 3595106.653 us (+73263.088 us / +2.080 %)
Median time: 3521843.565 us (1st quartile: 3448580.477 us | 3rd quartile: 3595106.653 us)
Average performance: 0.28394 iterations/s
Best performance: 0.28997 iterations/s (+0.00603 iterations/s / +2.12444 %)
Worst performance: 0.27816 iterations/s (-0.00579 iterations/s / -2.03786 %)
Median performance: 0.28394 iterations/s (1st quartile: 0.28997 | 3rd quartile: 0.27816)
[==========] Ran 5 benchmarks.
Check out the sources and use cmake
to build and install the project locally.
Install Boost
BOOST_VERSION=1.83.0
INSTALL_DIR=/usr/local/boost
cd /tmp
ver=`echo "${BOOST_VERSION}" | awk -F'.' '{printf("%d_%d_%d",$1,$2,$3)}'`
curl -OL https://boostorg.jfrog.io/artifactory/main/release/${BOOST_VERSION}/source/boost_${ver}.tar.bz2
tar xfj boost_${ver}.tar.bz2
sudo rm -rf $INSTALL_DIR
cd boost_${ver} \
&& ./bootstrap.sh \
&& sudo ./b2 -j8 cxxflags=-std=c++20 install link=static threading=multi runtime-link=static --prefix=$INSTALL_DIR --without-python --without-mpi
Install mongocxx driver
PREFIX=/usr/local/mongo
MONGOC_VERSION=1.24.2
MONGOCXX_VERSION=3.8.0
sudo rm -rf $PREFIX
cd /tmp
sudo rm -rf mongo-c-driver*
curl -L -O https://github.com/mongodb/mongo-c-driver/releases/download/${MONGOC_VERSION}/mongo-c-driver-${MONGOC_VERSION}.tar.gz
tar xzf mongo-c-driver-${MONGOC_VERSION}.tar.gz
cd /tmp/mongo-c-driver-${MONGOC_VERSION}
mkdir cmake-build && cd cmake-build
cmake \
-DENABLE_AUTOMATIC_INIT_AND_CLEANUP=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=$PREFIX \
-DCMAKE_INSTALL_LIBDIR=lib \
-DBUILD_SHARED_LIBS=OFF \
-DENABLE_SASL=OFF \
-DENABLE_TESTS=OFF \
-DENABLE_EXAMPLES=OFF \
..
make -j8
sudo make install
cd /tmp
sudo rm -rf mongo-cxx-driver
curl -OL https://github.com/mongodb/mongo-cxx-driver/releases/download/r${MONGOCXX_VERSION}/mongo-cxx-driver-r${MONGOCXX_VERSION}.tar.gz
tar -xzf mongo-cxx-driver-r${MONGOCXX_VERSION}.tar.gz
cd mongo-cxx-driver-r${MONGOCXX_VERSION}/build
cmake \
-DCMAKE_CXX_STANDARD=20 \
-DCMAKE_CXX_STANDARD_REQUIRED=ON \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_PREFIX_PATH=$PREFIX \
-DCMAKE_INSTALL_PREFIX=$PREFIX \
-DCMAKE_INSTALL_LIBDIR=lib \
-DBUILD_SHARED_LIBS=OFF \
-DCMAKE_TESTING_ENABLED=OFF \
-DENABLE_TESTS=OFF \
-DBSONCXX_POLY_USE_STD=ON \
..
make -j8
sudo make install
Check out, build and install the project.
cd /var/tmp
git clone https://github.com/sptrakesh/mongo-service.git
cd mongo-service
cmake -DCMAKE_BUILD_TYPE=Release \
-DCMAKE_PREFIX_PATH=/usr/local/boost \
-DCMAKE_PREFIX_PATH=/usr/local/mongo \
-DCMAKE_INSTALL_PREFIX=/usr/local/spt \
-DBUILD_TESTING=OFF -S . -B build
cmake --build build -j12
sudo cmake --install build
Install dependencies to build the project. The following instructions at times reference arm
or arm64
architecture. Modify
those values as appropriate for your hardware. These instructions are based on steps I followed to set up the project on a
Windows 11 virtual machine running via Parallels Desktop on a M2 Mac.
Install Boost
- Download and extract Boost 1.82 (or above) to a temporary location (eg.
\opt\src
). - Launch the Visual Studio Command utility and cd to the temporary location.
cd \opt\src
curl -OL https://boostorg.jfrog.io/artifactory/main/release/1.82.0/source/boost_1_82_0.tar.gz
tar -xfz boost_1_82_0.tar.gz
cd boost_1_82_0
.\bootstrap.bat
.\b2 -j8 install threading=multi address-model=64 architecture=arm asynch-exceptions=on --prefix=\opt\local --without-python --without-mpi
cd ..
del /s /q boost_1_82_0
rmdir /s /q boost_1_82_0
Install mongocxx driver
- Download Mongo C Driver (1.24.2 or above) and extract sources to a temporary location.
- Launch the Visual Studio Command utility and cd to the temporary location.
cd \opt\src
curl -OL https://github.com/mongodb/mongo-c-driver/releases/download/1.24.2/mongo-c-driver-1.24.2.tar.gz
tar -xfz mongo-c-driver-1.24.2.tar.gz
cd mongo-c-driver-1.24.2
cmake -DENABLE_AUTOMATIC_INIT_AND_CLEANUP=OFF -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=c:\opt\local -DBUILD_SHARED_LIBS=OFF -DENABLE_SASL=OFF -DENABLE_TESTS=OFF -DENABLE_EXAMPLES=OFF -S . -B cmake-build
cmake --build cmake-build --target install --parallel 8
cd ..
del /s /q mongo-c-driver-1.24.2
rmdir /s /q mongo-c-driver-1.24.2
- Downlaod Mongo CXX Driver (3.8 or above) and extract sources to a temporary location.
- Launch the Visual Studio Command utility and cd to the temporary location.
cd \opt\src
curl -OL https://github.com/mongodb/mongo-cxx-driver/releases/download/r3.8.0/mongo-cxx-driver-r3.8.0.tar.gz
tar -xvf mongo-cxx-driver-r3.8.0.tar.gz
cd mongo-cxx-driver-r3.8.0
cmake -DCMAKE_CXX_STANDARD=20 -DCMAKE_CXX_STANDARD_REQUIRED=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_PREFIX_PATH=c:\opt\local -DCMAKE_INSTALL_PREFIX=c:\opt\local -DCMAKE_INSTALL_LIBDIR=lib -DBUILD_SHARED_LIBS=OFF -DCMAKE_TESTING_ENABLED=OFF -DENABLE_TESTS=OFF -DBSONCXX_POLY_USE_STD=ON -S . -B build
cmake --build build --target install --parallel 8
cd ..
del /s /q mongo-cxx-driver-r3.8.0
rmdir /s /q mongo-cxx-driver-r3.8.0
Install fmt library
Launch the Visual Studio Command utility and cd to a temporary location.
cd \opt\src
git clone https://github.com/fmtlib/fmt.git --branch 9.1.0
cd fmt
cmake -DCMAKE_CXX_STANDARD=20 -DCMAKE_CXX_STANDARD_REQUIRED=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=\opt\local -DCMAKE_INSTALL_LIBDIR=lib -DFMT_TEST=OFF -DFMT_MODULE=ON -S . -B build
cmake --build build --target install -j8
Install range-v3 library
Launch the Visual Studio Command utility and cd to a temporary location.
git clone https://github.com/ericniebler/range-v3.git --branch 0.12.0
cd range-v3
cmake -DCMAKE_CXX_STANDARD=20 -DCMAKE_CXX_STANDARD_REQUIRED=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=\opt\local -DCMAKE_INSTALL_LIBDIR=lib -DRANGE_V3_DOCS=OFF -DRANGE_V3_EXAMPLES=OFF -DRANGE_V3_PERF=OFF -DRANGE_V3_TESTS=OFF -DRANGE_V3_INSTALL=ON -B build -S .
cmake --build build --target install -j8
Install vcpkg manager
Launch the Visual Studio Command utility.
cd \opt\src
git clone https://github.com/Microsoft/vcpkg.git
cd vcpkg
.\bootstrap-vcpkg.bat -disableMetrics
.\vcpkg integrate install --vcpkg-root \opt\src\vcpkg
.\vcpkg install curl:arm64-windows
.\vcpkg install cpr:arm64-windows
Check out, build and install the project.
Launch the Visual Studio Command utility.
cd %homepath%\source\repos
git clone https://github.com/sptrakesh/mongo-service.git
cd mongo-service
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_PREFIX_PATH=\opt\local -DCMAKE_INSTALL_PREFIX=\opt\spt -DBUILD_TESTING=ON -DCMAKE_TOOLCHAIN_FILE="C:/opt/src/vcpkg/scripts/buildsystems/vcpkg.cmake" -S . -B build
cmake --build build -j8
cmake --build build --target install
Run the service by specifying options similar to the following:
cd %homepath%\source\repos\mongo-service
build\src\service\Debug\mongo-service.exe -e true -o %temp%\ -p 2020 -m "mongodb://test:test@192.168.0.39/admin?authSource=admin&compressors=snappy&w=1" -l debug --metric-batch-size 2
Run other targets such as unitTest
, integration
, client
as appropriate directly from the IDE.
The following limitations have been encountered when running the test suites. A few tests have been disabled when running on Windows to avoid running into these issues.
- Cannot create an index with a specific name. For some reason, this leads to the index name being stored with non-UTF-8 characters, which then causes further issues down the road.
Sample clients in other languages that use the service.
- Julia - Sample client package for Julia is available under the julia directory.
- Python - Sample client package for Python is available under the python directory.
The API can be used to communicate with the TCP service. Client code bases can use cmake to use the library.
# In your CMakeLists.txt file
find_package(MongoService REQUIRED COMPONENTS api)
if (APPLE)
include_directories(/usr/local/spt/include)
else()
include_directories(/opt/spt/include)
endif (APPLE)
target_link_libraries(${Target_Name} PRIVATE mongo-service::api ...)
# Run cmake
cmake -DCMAKE_PREFIX_PATH=/usr/local/boost -DCMAKE_PREFIX_PATH=/usr/local/mongo -DCMAKE_PREFIX_PATH=/usr/local/spt -S . -B build
cmake --build build -j12
This software has been developed mainly using work other people/projects have contributed. The following are the components used to build this software:
- Boost:Asio - We use Asio for the
TCP socket
server implementation. - MongoCXX - MongoDB C++ driver.
- **magic_enum - Static reflection for enums.
- visit_struct - Struct visitor library used for the serialisation utility functions.
- concurrentqueue - Lock free concurrent queue implementation for metrics.
- NanoLog - Logging framework used for the server. I modified the implementation for daily rolling log files.
- Catch2 - Unit testing framework.
- Clara - Command line options parser.
- hayai - Performance testing framework.