A-REX data transfer framework (DTR) technical description¶
This page describes the data staging framework for ARC, code-named DTR (Data Transfer Reloaded).
ARC’s Computing Element (A-REX) performs the task of data transfer for jobs before and after the jobs run. The requirements and the design steps for the data staging framework are described in DTR Design and Implementation Details. The framework is called DTR (Data Transfer Reloaded) and uses a three-layer architecture, shown in the figure below:
The Generator uses user input of tasks to construct a Data Transfer Request (also DTR) per file that needs to be transferred. These DTRs are sent to the Scheduler for processing. The Scheduler sends DTRs to the Pre-processor for anything that needs to be done up until the physical transfer takes place (e.g. cache check, resolve replicas) and then to Delivery for the transfer itself. Once the transfer has finished the Post-processor handles any post-transfer operations (e.g. register replicas, release requests). The number of slots available for each component is limited, so the Scheduler controls queues and decides when to allocate slots to specific DTRs, based on the prioritisation algorithm implemented. See DTR priority and shares system for more information.
This layered architecture allows any implementation of a particular component to be easily substituted for another, for example a GUI with which users can enter DTRs (Generator) or an external point-to-point file transfer service (Delivery).
The middle and lower layers of the architecture (Scheduler, Processor
and Delivery) are implemented as a separate library
src/libs/data-staging in the ARC source tree).
This library is included in the nordugrid-arc common libraries
package. It depends on some other common ARC libraries and the DMC
modules (which enable various data access protocols and are included in
nordugrid-arc-plugins-* packages) but is independent of other
components such as A-REX or ARC clients. A simple Generator is included
in this library for testing purposes. A Generator for A-REX is
turns job descriptions into data transfer requests.
Data staging is configured through the
[arex/data-staging] block in arc.conf.
Reasonable default values exist for all parameters but the
[arex/data-staging] block can be used to tune the parameters,
and also enable multi-host data staging. A selection of
parameters are shown below:
|maxdelivery||Maximum delivery slots||10|
|maxprocessor||Maximum processor slots per state||10|
|maxemergency||Maximum emergency slots for delivery and processor||1|
|maxprepared||Maximum prepared files (for example pinned files using SRM)||200|
|sharetype||Transfer share scheme (dn, voms:vo, voms:group or voms:role)||None|
|definedshare||Defined share and priority||_default 50|
|Multi-host related parameters|
|deliveryservice||URL of remote host which can perform data delivery||None|
|localdelivery||Whether local delivery should also be done||no|
|remotesizelimit||File size limit (in bytes) below which local transfer is always used||0|
|usehostcert||Whether the host certificate should be used in communication with remote delivery services instead of the user’s proxy||no|
[data-staging] maxdelivery = 10 maxprocessor = 20 maxemergency = 2 maxprepared = 50 sharetype = voms:role definedshare = myvo:production 80 deliveryservice = https://spare.host:60003/datadeliveryservice localdelivery yes remotesizelimit = 1000000
To specify the priority of jobs on the client side, the
element can be added to an XRSL job description, eg:
("priority" = "80")
For a full explanation of how priorities work see DTR priority and shares system.
The command “gm-jobs -s” to show transfer shares information now shows the same information at the per-file level rather than per-job. The number in “Preparing” are the number of DTRs in TRANSFERRING state, i.e. doing physical transfer. Other DTR states count towards the “Pending” files. For example:
Preparing/Pending files Transfer share 2/86 atlas:null-download 3/32 atlas:production-download
As before, per-job logging information is in the controldir/job.id.errors files,
but A-REX can also be configured to log all DTR messages to a central log file
in addition through the
Using DTR in third-party applications¶
ARC SDK Documentation gives examples on how to integrate DTR in third-party applications.
The following access and transfer protocols are supported. Note that third-party transfer is not supported.
- RFIO/DCAP/LFC (through GFAL2 plugins)
Multi-host Data Staging¶
To increase overall bandwidth, multiple hosts can be used to perform the physical transfers. See ARC Data Delivery Service Technical Description for details.
In A-REX the state, priority and share of all DTRs is logged to the file controldir/dtr.state periodically (every second). This can then used by the Gangliarc framework to show data staging information as ganglia metrics.
DTR offers many advantages over the previous system, including:
- High performance
- When a transfer finishes in Delivery, there is always another prepared and ready, so the network is always fully used. A file stuck in a pre-processing step does not block others preparing or affect any physical transfers running or queued. Cached files are processed instantly rather than waiting behind those needing transferred. Bulk calls are implemented for some operations of indexing catalogs and SRM protocols.
- All state is held in memory, which enables extremely fast queue processing. The system knows which files are writing to cache and so does not need to constantly poll the file system for lock files.
- When a DTR is cancelled mid-transfer, the destination file is deleted and all resources such as SRM pins and cache locks are cleaned up before returning the DTR to the Generator. On A-REX shutdown all DTRs can be cleanly cancelled in this way.
- Fault tolerance
- The state of the system is frequently dumped to a file, so in the event of crash or power cut, this file can be read to recover the state of ongoing transfers. Transfers stopped mid-way are automatically restarted after cleaning up the half-finished attempt.
- Error handling has vastly improved so that temporary errors caused by network glitches, timeouts, busy remote services etc are retried transparently.
- Both the server admins and users have control over which data transfers have which priority.
- Admins can see at a glance the state of the system and using a standard framework like Ganglia means admins can monitor ARC in the same way as the rest of their system.
- An arbitrary number of extra hosts can be easily added to the system to scale up the bandwidth available. The system has been tested with up to tens of thousands of concurrent DTRs.
- The system can run with no configuration changes, or many detailed options can be tweaked.
- Generic flexible framework
- The framework is not specific to ARC’s Computing Element (A-REX) and can be used by any generic data transfer application.
- Provide a way for the infosys to obtain DTR status information
- First basic implementation: when DTR changes state write current state to .input or .output file
- Decide whether or not to cancel all DTRs in a job when one fails
- Current logic: if downloading, cancel all DTRs in job, if uploading don’t cancel any
- Should be configurable by user - also EMI execution service interface allows specifying per-file what to do in case of error
- Priorities: more sophisticated algorithms for handling priorities
- Advanced features such as pausing and resuming transfers