Many task computing with distributed file system

• US 10,650,046 B2
• Filed: 09/30/2019
• Issued: 05/12/2020
• Est. Priority Date: 02/05/2016
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Bequet, Henry Gabriel Victor, Yang, Eric Jian, Stogner, Ronald Earl, Zhang, Chaowang "Ricky", Dutta, Partha, Gong, Qing
• Primary Examiner(s): Patel, Hiren P
• Application Number:
  US16/587,965
• Publication Number:
  US 20200026732A1
• Time in Patent Office: 225 Days
• Field of Search: None
• CPC Class Codes: G06F 16/164 File meta data generation
• CPC Class Codes: G06F 16/1727 Details of free space management performed by the file system saving storage space on storage systems G06F3/0608; management of blocks in storage devices G06F3/064
• CPC Class Codes: G06F 16/182 Distributed file systems
• CPC Class Codes: G06F 16/1827 Management specifically adapted to NAS management of storage area networks [SAN] G06F3/067
• CPC Class Codes: G06F 16/9014 hash tables
• CPC Class Codes: G06F 16/90344 by using string matching techniques
• CPC Class Codes: G06F 8/51 Source to source
• CPC Class Codes: G06F 9/46 Multiprogramming arrangements
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06N 3/044 Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: G06N 3/045 Combinations of networks
• CPC Class Codes: G06N 3/063 using electronic means
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/1097 for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/55 : Push-based network services

Abstract

An apparatus includes a processor to: receive a request from a remote device to perform a job flow; retrieve a job flow definition defining the job flow and each of a set of task routines to perform tasks of the job flow from a set of storage devices where each is stored as an undivided object within one storage device; and in response to determining that a data set is stored as multiple data object blocks, generate a container containing the job flow definition and set of task routines to enable each storage device to perform the job flow using a locally stored data object block of the data set as input to generate a corresponding data object block of a result report, provide a copy of the container to each storage device, and transmit the result report assembled from the data object blocks thereof to the remote device.

Claims

1. An apparatus comprising a processor and a storage to store instructions that, when executed by the processor, cause the processor to perform operations comprising:

receive, at the processor and from a remote device, a request to perform a job flow using a flow input data set as an input to the job flow performance, wherein;

the job flow is defined in a job flow definition that specifies a set of tasks to be performed via execution of a corresponding set of task routines during the job flow performance;

at least one result report is to be generated as an output of the job flow performance;

the job flow definition and each task routine of the set of task routines is stored as an undivided object within one storage device of a set of storage devices;

the flow input data set is either stored as an undivided object within one storage device of the set of storage devices, or stored as a set of data object blocks into which the flow input data set is divided and distributed among the set of storage devices;

each storage device of the set of storage devices incorporates a processor;

the processors of the set of storage devices cooperate to maintain a distributed file system that spans storage spaces provided by each storage device of the set of storage devices;

as part of maintaining the distributed file system, at least one processor of at least one storage device of the set of storage devices determines whether a data object received by the set of storage devices is to be stored as an undivided object or stored as a set of data object blocks into which the received data object is divided and distributed among the set of storage devices based on a size of the received data object compared to a distribution block size; and

the flow input data set is stored as a set of data object blocks of the flow input data set by the set of storage devices in response to the flow input data set having a size larger than the distribution block size;

retrieve the job flow definition and each task routine of the set of task routines from the set of storage devices;

determine whether the flow input data set is stored as an undivided object or as a set of data object blocks based on the size of the flow input data set; and

in response to a determination that the flow input data set is stored as a set of data objects blocks, the processor is caused to perform operations comprising;

generate a container that contains the job flow definition and the set of task routines to enable the processor incorporated into each storage device to independently perform an instance of the job flow using one of the data object blocks of the flow input data set stored locally within the storage device as an input to the instance, wherein the performance of an instance of the job flow within each storage device generates a corresponding data object block of a set of data object blocks of the result report;

provide a copy of the container to each storage device of the set of storage devices to enable the processors incorporated into least two storage devices of the set of storage devices to perform instances of the job flow at least partially in parallel;

retrieve, from each storage device of the set of storage devices, at least one data object block of the set of data object blocks of the result report;

assemble the result report from the set of data object blocks of the result report; and

transmit the result report to the remote device.

2. The apparatus of claim 1, wherein the processor is caused to perform operations comprising:

retrieve, from the set of storage devices, an indication of the distribution block size;

define a predetermined threshold size based on the distribution block size; and

at a time prior to the performance of the job flow, the processor is caused to perform operations comprising;

compare a size of the flow input data set to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the flow input data set is larger than the predetermined threshold size, the processor is caused to perform operations comprising;

analyze the flow input data set to determine whether the flow input data set is of a distributable form in which there is no distinct metadata structure therein, and in which data items of the flow input data set are organized into a single homogeneous data structure wherein the data items remain accessible from each data object block of the flow input data set independently of the other data object blocks after the division of the flow input data set; and

in response to a determination that the flow input data set is not of the distributable form of the flow input data set, convert the flow input data set into the distributable form of the flow input data set prior to the storage of the flow input data set by the set of storage devices.

3. The apparatus of claim 2, wherein:

the distributed file system comprises Hadoop distributed file system (HDFS); and

the distributable form of the flow input data set is selected from a group consisting of;

a text file comprising data items separated by delimiters; and

a optimized row columnar (ORC) file comprising compressed data items.

4. The apparatus of claim 2, wherein the processor is caused to perform operations comprising:

compare a size of the result report to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the result report is larger than the predetermined threshold size, the processor is caused to perform operations comprising;

analyze the result report to determine whether the result report is of a distributable form;

in response to a determination that the result report is not of the distributable form of the result report, convert the result report into the distributable form of the result report; and

provide the distributable form of the result report to the set of storage devices to be divided into the set of data object blocks of the result report that are to be distributed among the set of storage devices.

5. The apparatus of claim 4, wherein:

the job flow definition, each task routine of the set of task routines, the flow input data set and the result report are each stored within a federated area of a set of federated areas that is maintained by the set of storage devices and that the remote device is authorized to access; and

the federated area in which at least the flow input data set is stored is defined to span the multiple storage devices within the distributed file system.

6. The apparatus of claim 1, wherein the processor is caused, in response to a determination that the flow input data set is stored as an undivided object within one storage device of the set of storage devices, to perform operations comprising:

retrieve the flow input data set from the set of storage devices;

perform the job flow using the flow input data set as an input to generate the result report; and

transmit the result report to the remote device.

7. The apparatus of claim 1, wherein:

the performance of at least one task of the job flow comprises instantiating a neural network for use in performing the job flow based on neural network configuration data stored within a mid-flow data set;

the mid-flow data set is stored as an undivided object within one storage device of the set of storage devices; and

the processor is caused to perform operations comprising;

retrieve the mid-flow data set from the set of storage devices; and

in response to the determination that the flow input data set is stored as a set of data objects blocks, the processor is caused to generate the container to additionally contain the mid-flow data set to enable the processor of each storage device to use the mid-flow data set to independently instantiate an instance of the neural network for use performing a corresponding instance of the job flow based on the neural network configuration data within the mid-flow data set.

8. The apparatus of claim 7, wherein each storage device of the set of storage devices comprises at least one neuromorphic device capable of instantiating the neural network based on the neural network configuration data within the mid-flow data set.

9. The apparatus of claim 1, wherein the processor is caused to perform operations comprising:

receive, at the processor, another request to store the flow input data set in a federated of a set of federated areas, wherein;

the set of federated area is defined within storage space of the distributed file system to store objects required to perform the job flow; and

the objects required to perform the job flow comprise the job flow definition, and the set of task routines;

retrieve, from the set of storage devices, an indication of the distribution block size;

define a predetermined threshold size based on the distribution block size;

compare the size of the flow input data set to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the flow input data set is larger than the predetermined threshold size, the processor is caused to perform operations comprising;

analyze the flow input data set to determine whether the flow input data set is of a distributable form in which data items of the flow input data set are organized into a single homogeneous data structure, wherein after the flow input data set is divided into a set of data object blocks, the data items remain accessible from each data object block of the flow input data set independently of the other data object blocks of the flow input data set;

in response to a determination that the flow input data set is not of the distributable form of the flow input data set, convert the flow input data set into the distributable form of the flow input data set; and

provide the distributable form of the flow input data set to the set of storage devices to be divided into the set of data object blocks of the flow input data set that are to be distributed among the set of storage devices and within a first federated area of the set of federated areas, wherein the first federated area is defined within the storage space of the distributed file system.

10. The apparatus of claim 9, wherein the processor is caused, in response to a determination that the size of the flow input data set is smaller than the predetermined threshold size, to provide the flow input data set to the set of storage devices to be stored as an undivided object within storage space provided by a single storage device of the set of storage devices, and within in a federated area selected from a set consisting of:

the first federated area defined within the storage space of the distributed file system; and

a second federated area defined within storage space of a local file system maintained by one storage device of the set of storage devices.

11. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions operable to cause a processor to perform operations comprising:

receive, at the processor and from a remote device, a request to perform a job flow using a flow input data set as an input to the job flow performance, wherein;

the job flow is defined in a job flow definition that specifies a set of tasks to be performed via execution of a corresponding set of task routines during the job flow performance;

at least one result report is to be generated as an output of the job flow performance;

the job flow definition and each task routine of the set of task routines is stored as an undivided object within one storage device of a set of storage devices;

the flow input data set is either stored as an undivided object within one storage device of the set of storage devices, or stored as a set of data object blocks into which the flow input data set is divided and distributed among the set of storage devices;

each storage device of the set of storage devices incorporates a processor;

the processors of the set of storage devices cooperate to maintain a distributed file system that spans storage spaces provided by each storage device of the set of storage devices;

as part of maintaining the distributed file system, at least one processor of at least one storage device of the set of storage devices determines whether a data object received by the set of storage devices is to be stored as an undivided object or stored as a set of data object blocks into which the received data object is divided and distributed among the set of storage devices based on a size of the received data object compared to a distribution block size; and

the flow input data set is stored as a set of data object blocks of the flow input data set by the set of storage devices in response to the flow input data set having a size larger than the distribution block size;

retrieve the job flow definition and each task routine of the set of task routines from the set of storage devices;

determine whether the flow input data set is stored as an undivided object or as a set of data object blocks based on the size of the flow input data set; and

in response to a determination that the flow input data set is stored as a set of data objects blocks, the processor is caused to perform operations comprising;

generate a container that contains the job flow definition and the set of task routines to enable the processor incorporated into each storage device to independently perform an instance of the job flow using one of the data object blocks of the flow input data set stored locally within the storage device as an input to the instance, wherein the performance of an instance of the job flow within each storage device generates a corresponding data object block of a set of data object blocks of the result report;

provide a copy of the container to each storage device of the set of storage devices to enable the processors incorporated into least two storage devices of the set of storage devices to perform instances of the job flow at least partially in parallel;

retrieve, from each storage device of the set of storage devices, at least one data object block of the set of data object blocks of the result report;

assemble the result report from the set of data object blocks of the result report; and

transmit the result report to the remote device.

12. The computer-program product of claim 11, wherein the processor is caused to perform operations comprising:

retrieve, from the set of storage devices, an indication of the distribution block size;

define a predetermined threshold size based on the distribution block size; and

at a time prior to the performance of the job flow, the processor is caused to perform operations comprising;

compare a size of the flow input data set to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the flow input data set is larger than the predetermined threshold size, the processor is caused to perform operations comprising;

analyze the flow input data set to determine whether the flow input data set is of a distributable form in which there is no distinct metadata structure therein, and in which data items of the flow input data set are organized into a single homogeneous data structure wherein the data items remain accessible from each data object block of the flow input data set independently of the other data object blocks after the division of the flow input data set; and

in response to a determination that the flow input data set is not of the distributable form of the flow input data set, convert the flow input data set into the distributable form of the flow input data set prior to the storage of the flow input data set by the set of storage devices.

13. The computer-program product of claim 12, wherein:

the distributed file system comprises Hadoop distributed file system (HDFS); and

the distributable form of the flow input data set is selected from a group consisting of;

a text file comprising data items separated by delimiters; and

a optimized row columnar (ORC) file comprising compressed data items.

14. The computer-program product of claim 12, wherein the processor is caused to perform operations comprising:

compare a size of the result report to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the result report is larger than the predetermined threshold size, the processor is caused to perform operations comprising;

analyze the result report to determine whether the result report is of a distributable form;

in response to a determination that the result report is not of the distributable form of the result report, convert the result report into the distributable form of the result report; and

provide the distributable form of the result report to the set of storage devices to be divided into the set of data object blocks of the result report that are to be distributed among the set of storage devices.

15. The computer-program product of claim 14, wherein:

the job flow definition, each task routine of the set of task routines, the flow input data set and the result report are each stored within a federated area of a set of federated areas that is maintained by the set of storage devices and that the remote device is authorized to access; and

the federated area in which at least the flow input data set is stored is defined to span the multiple storage devices within the distributed file system.

16. The computer-program product of claim 11, wherein the processor is caused, in response to a determination that the flow input data set is stored as an undivided object within one storage device of the set of storage devices, to perform operations comprising:

retrieve the flow input data set from the set of storage devices;

perform the job flow using the flow input data set as an input to generate the result report; and

transmit the result report to the remote device.

17. The computer-program product of claim 11, wherein:

the performance of at least one task of the job flow comprises instantiating a neural network for use in performing the job flow based on neural network configuration data stored within a mid-flow data set;

the mid-flow data set is stored as an undivided object within one storage device of the set of storage devices; and

the processor is caused to perform operations comprising;

retrieve the mid-flow data set from the set of storage devices; and

in response to the determination that the flow input data set is stored as a set of data objects blocks, the processor is caused to generate the container to additionally contain the mid-flow data set to enable the processor of each storage device to use the mid-flow data set to independently instantiate an instance of the neural network for use performing a corresponding instance of the job flow based on the neural network configuration data within the mid-flow data set.

18. The computer-program product of claim 17, wherein each storage device of the set of storage devices comprises at least one neuromorphic device capable of instantiating the neural network based on the neural network configuration data within the mid-flow data set.

19. The computer-program product of claim 11, wherein the processor is caused to perform operations comprising:

receive, at the processor, another request to store the flow input data set in a federated of a set of federated areas, wherein;

the set of federated area is defined within storage space of the distributed file system to store objects required to perform the job flow; and

the objects required to perform the job flow comprise the job flow definition, and the set of task routines;

retrieve, from the set of storage devices, an indication of the distribution block size;

define a predetermined threshold size based on the distribution block size;

compare the size of the flow input data set to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the flow input data set is larger than the predetermined threshold size, the processor is caused to perform operations comprising;

analyze the flow input data set to determine whether the flow input data set is of a distributable form in which data items of the flow input data set are organized into a single homogeneous data structure, wherein after the flow input data set is divided into a set of data object blocks, the data items remain accessible from each data object block of the flow input data set independently of the other data object blocks of the flow input data set;

in response to a determination that the flow input data set is not of the distributable form of the flow input data set, convert the flow input data set into the distributable form of the flow input data set; and

provide the distributable form of the flow input data set to the set of storage devices to be divided into the set of data object blocks of the flow input data set that are to be distributed among the set of storage devices and within a first federated area of the set of federated areas, wherein the first federated area is defined within the storage space of the distributed file system.

20. The computer-program product of claim 19, wherein the processor is caused, in response to a determination that the size of the flow input data set is smaller than the predetermined threshold size, to provide the flow input data set to the set of storage devices to be stored as an undivided object within storage space provided by a single storage device of the set of storage devices, and within in a federated area selected from a set consisting of:

the first federated area defined within the storage space of the distributed file system; and

a second federated area defined within storage space of a local file system maintained by one storage device of the set of storage devices.

21. A computer-implemented method comprising:

receiving, by a processor, and from a remote device, a request to perform a job flow using a flow input data set as an input to the job flow performance, wherein;

the job flow is defined in a job flow definition that specifies a set of tasks to be performed via execution of a corresponding set of task routines during the job flow performance;

at least one result report is to be generated as an output of the job flow performance;

the job flow definition and each task routine of the set of task routines is stored as an undivided object within one storage device of a set of storage devices;

the flow input data set is either stored as an undivided object within one storage device of the set of storage devices, or stored as a set of data object blocks into which the flow input data set is divided and distributed among the set of storage devices;

each storage device of the set of storage devices incorporates a processor;

the processors of the set of storage devices cooperate to maintain a distributed file system that spans storage spaces provided by each storage device of the set of storage devices;

as part of maintaining the distributed file system, at least one processor of at least one storage device of the set of storage devices determines whether a data object received by the set of storage devices is to be stored as an undivided object or stored as a set of data object blocks into which the received data object is divided and distributed among the set of storage devices based on a size of the received data object compared to a distribution block size; and

the flow input data set is stored as a set of data object blocks of the flow input data set by the set of storage devices in response to the flow input data set having a size larger than the distribution block size;

retrieving the job flow definition and each task routine of the set of task routines from the set of storage devices;

determining, by the processor, whether the flow input data set is stored as an undivided object or as a set of data object blocks based on the size of the flow input data set; and

in response to a determination that the flow input data set is stored as a set of data objects blocks, performing operations comprising;

generating, by the processor, a container that contains the job flow definition and the set of task routines to enable the processor incorporated into each storage device to independently perform an instance of the job flow using one of the data object blocks of the flow input data set stored locally within the storage device as an input to the instance, wherein the performance of an instance of the job flow within each storage device generates a corresponding data object block of a set of data object blocks of the result report;

providing a copy of the container to each storage device of the set of storage devices to enable the processors incorporated into least two storage devices of the set of storage devices to perform instances of the job flow at least partially in parallel;

retrieving, from each storage device of the set of storage devices, at least one data object block of the set of data object blocks of the result report;

assembling, by the processor, the result report from the set of data object blocks of the result report; and

transmitting, from the processor, the result report to the remote device;

or

in response to a determination that the flow input data set is stored as an undivided object within one storage device of the set of storage devices, performing operations comprising;

retrieving the flow input data set from the set of storage devices;

performing, by the processor, the job flow using the flow input data set as an input to generate the result report; and

transmitting, from the processor, the result report to the remote device.

22. The computer-implemented method of claim 21, comprising:

retrieving, from the set of storage devices, an indication of the distribution block size;

defining, by the processor, a predetermined threshold size based on the distribution block size; and

at a time prior to the performance of the job flow, performing operations comprising;

comparing, by the processor, a size of the flow input data set to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the flow input data set is larger than the predetermined threshold size, performing operations comprising;

analyzing, by the processor, the flow input data set to determine whether the flow input data set is of a distributable form in which there is no distinct metadata structure therein, and in which data items of the flow input data set are organized into a single homogeneous data structure wherein the data items remain accessible from each data object block of the flow input data set independently of the other data object blocks after the division of the flow input data set; and

in response to a determination that the flow input data set is not of the distributable form of the flow input data set, converting, by the processor, the flow input data set into the distributable form of the flow input data set prior to the storage of the flow input data set by the set of storage devices.

23. The computer-implemented method of claim 22, wherein:

the distributed file system comprises Hadoop distributed file system (HDFS); and

the distributable form of the flow input data set is selected from a group consisting of;

a text file comprising data items separated by delimiters; and

a optimized row columnar (ORC) file comprising compressed data items.

24. The computer-implemented method of claim 22, comprising:

comparing, by the processor, a size of the result report to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the result report is larger than the predetermined threshold size, performing operations comprising;

analyzing, by the processor, the result report to determine whether the result report is of a distributable form;

in response to a determination that the result report is not of the distributable form of the result report, converting, by the processor, the result report into the distributable form of the result report; and

providing the distributable form of the result report to the set of storage devices to be divided into the set of data object blocks of the result report that are to be distributed among the set of storage devices.

25. The computer-implemented method of claim 24, wherein:

the job flow definition, each task routine of the set of task routines, the flow input data set and the result report are each stored within a federated area of a set of federated areas that is maintained by the set of storage devices and that the remote device is authorized to access; and

the federated area in which at least the flow input data set is stored is defined to span the multiple storage devices within the distributed file system.

26. The computer-implemented method of claim 24, comprising, in response to a determination that the size of the result report is smaller than the predetermined threshold size, providing the result report to the set of storage devices to be stored as an undivided object within storage space provided by one storage device of the set of storage devices.

27. The computer-implemented method of claim 21, wherein:

the performance of at least one task of the job flow comprises instantiating a neural network for use in performing the job flow based on neural network configuration data stored within a mid-flow data set;

the mid-flow data set is stored as an undivided object within one storage device of the set of storage devices; and

the method comprises;

retrieving the mid-flow data set from the set of storage devices; and

in response to the determination that the flow input data set is stored as a set of data objects blocks, generating, by the processor, the container to additionally contain the mid-flow data set to enable the processor of each storage device to use the mid-flow data set to independently instantiate an instance of the neural network for use performing a corresponding instance of the job flow based on the neural network configuration data within the mid-flow data set.

28. The computer-implemented method of claim 27, wherein each storage device of the set of storage devices comprises at least one neuromorphic device capable of instantiating the neural network based on the neural network configuration data within the mid-flow data set.

29. The computer-implemented method of claim 21, comprising:

receiving, by the processor, another request to store the flow input data set in a federated of a set of federated areas, wherein;

the set of federated area is defined within storage space of the distributed file system to store objects required to perform the job flow; and

the objects required to perform the job flow comprise the job flow definition, and the set of task routines;

retrieving, from the set of storage devices, an indication of the distribution block size;

defining, by the processor, a predetermined threshold size based on the distribution block size;

comparing, by the processor, the size of the flow input data set to the predetermined threshold size to determine whether the size of the flow input data set is larger than the predetermined threshold size; and

in response to a determination that the size of the flow input data set is larger than the predetermined threshold size, performing operations comprising;

analyzing, by the processor, the flow input data set to determine whether the flow input data set is of a distributable form in which data items of the flow input data set are organized into a single homogeneous data structure, wherein after the flow input data set is divided into a set of data object blocks, the data items remain accessible from each data object block of the flow input data set independently of the other data object blocks of the flow input data set;

in response to a determination that the flow input data set is not of the distributable form of the flow input data set, converting, by the processor, the flow input data set into the distributable form of the flow input data set; and

providing the distributable form of the flow input data set to the set of storage devices to be divided into the set of data object blocks of the flow input data set that are to be distributed among the set of storage devices and within a first federated area of the set of federated areas, wherein the first federated area is defined within the storage space of the distributed file system.

30. The computer-implemented method of claim 29, comprising, in response to a determination that the size of the flow input data set is smaller than the predetermined threshold size, providing the flow input data set to the set of storage devices to be stored as an undivided object within storage space provided by a single storage device of the set of storage devices, and within in a federated area selected from a set consisting of:

the first federated area defined within the storage space of the distributed file system; and

a second federated area defined within storage space of a local file system maintained by one storage device of the set of storage devices.