KR101918662B1 - Method and apparatus for the fast analysis of large-scale scientific data files - Google Patents

Abstract

 The present invention relates to large scale scientific data instant analysis methods and apparatus. The present invention relates to a method capable of directly processing a query without data loading on scientific experiment data modeled as a multidimensional array. The mass scientific data instant analysis apparatus according to an embodiment of the present invention includes a file merge unit for merging scientific data files according to the number of nodes where an instance of a database is located, and the merged scientific data files are arranged in an array structure in the database A global map processing unit for rearranging the arranged scientific data files according to an original data loading manner of the database, and a query processing unit for performing a query processing on the relocated scientific data files do.

Description

METHOD AND APPARATUS FOR THE FAST ANALYSIS OF LARGE-SCALE SCIENTIFIC DATA FILES FIELD OF THE INVENTION [0001]

The present invention relates to a method and apparatus for instant analysis of large capacity scientific data files.

 Previously, scientific experiment data was archived and distributed as one file along with metadata providing information about the experiment. For data analysis, the file should be read and loaded into the DB, but it takes a very long time to load . Accordingly, there is a problem that the total time from the actual file acquisition time to the completion of the query processing using the DB is very long. Furthermore, analysis queries on scientific data are not frequent, so existing DBs designed to assume frequent queries after loading are not suitable.

 In addition, scientific data contains observations or observations of various phenomena in the real world, and often has a multi-dimensional array. For example, the satellite photographed image information is information in which an image value photographed at a specific position at a specific time is recorded. That is, the image information for a cell on a three-dimensional (latitude, longitude, and time) basis is composed of RGB values. Such a multidimensional array structure is difficult to support efficient storage and retrieval with existing relational DBMSs that store data in a two-dimensional table format. As a result, a multi-dimensional array DBMS for efficiently storing multi-dimensional arrays has appeared. Scientific data, on the other hand, is created in a way that contains both experimental data and metadata in a single file format for ease of maintenance and distribution.

 Loading these scientific data files into a multidimensional array DBMS takes a lot of time. As a result, the total time taken to process analytical queries after obtaining the actual scientific data file takes a long time due to the data loading time. Scientific data does not frequently query the generated data due to its nature. Accordingly, a lot of time and resources are wasted in the process of loading data that is not frequently processed in the DB.

 On the other hand, scientific data created and / or distributed in the scientific data file format is so large that one file costs hundreds of gigabytes. When processing such large files on a single system with per-file APIs, the processing performance is not scalable due to input / output (I / O) and computing constraints on a single node.

 SUMMARY OF THE INVENTION The present invention provides a method for instantly analyzing large-scale scientific data files.

 It is an object of the present invention to provide a method of directly analyzing and processing a query on a large scale scientific data file without data loading process.

 Disclosure of Invention Technical Problem [8] The present invention provides a method for directly analyzing large-capacity multi-dimensional scientific data files on a file without performing data loading and distributing and / or parallelly processing queries.

 SUMMARY OF THE INVENTION The present invention provides a method for efficient parallel query processing of a large scale scientific data file composed of a multi-dimensional array in a distributed environment.

 SUMMARY OF THE INVENTION It is an object of the present invention to provide a method of omitting a data loading process and directly performing a distributed parallel processing of a query word on multidimensional array data on a file.

 According to an aspect of the present invention, there is provided a method for instantly analyzing large-scale scientific data, comprising merging scientific data files according to the number of nodes in which instances of a database are located, arranging the merged science data files in an array structure in the database, And relocating the placed scientific data files according to the original data loading method of the database and / or querying the relocated scientific data files.

 Advantageously, the merging step merges a plurality of scientific data files having the same structure by the number of nodes to merge them into larger sized scientific data files, wherein one of the merged science data files The size may not exceed the available memory size of the node.

 Advantageously, the step of arranging comprises the steps of filtering the merged scientific data files so as to process only the scientific data that is the direct object of the query, not all data, processing the filtered scientific data files, and / Or generating a multidimensional array on the memory in units of nodes on the read-processed scientific data files.

 Advantageously, the step of generating the multidimensional array comprises: using the chunk identification information of the read-processed scientific data files and the location information in the chunks, As shown in FIG.

 Advantageously, the step of relocating comprises: allocating chunks of scientific data files to be located at different nodes according to the original data loading scheme of the database among the chunks of the science data files located in the memory of each of the nodes, , ≪ / RTI > receiving chunks of scientific data files to be located at the other nodes that have passed and / or merging chunks of the received scientific data files with chunks of already placed science data files .

 Advantageously, the mass scientific data instant analysis method may include storing the queried scientific data files according to the original data loading scheme of the database.

 A large scale scientific data instant analysis apparatus according to another embodiment of the present invention includes a file merge unit for merging scientific data files according to the number of nodes where an instance of a database is located, A global map processing unit for rearranging the arranged scientific data files according to an original data loading method of the database, and a global map processing unit for performing a query processing on the relocated scientific data files And a query processing unit.

 Preferably, the file merging unit merges a plurality of scientific data files having the same structure by the number of nodes, and merges the same into scientific data files of a larger size, wherein the size of one of the merged science data files May not exceed the available memory size of the node.

 Preferably, the local map processing unit includes a filtering processing unit for filtering the merged scientific data files so as to process only the scientific data that is a direct object of the inquiry, not all of the data, a reading processing unit for reading the filtered scientific data files, And a building processor for generating a multidimensional array on the memory in units of the nodes on the basis of the read-processed scientific data files.

 Advantageously, the building processor may place the read-processed scientific data files into specific chunks in the database using chunk identification information of the read-processed scientific data files and location information within the chunks. have.

 Preferably, the global map processing unit allocates chunks of scientific data files to be located at different nodes to other nodes according to the original data loading method of the database among the chunks of the science data files disposed in the memory of each of the nodes A gather processing unit for receiving chunks of scientific data files to be located at the other nodes and / or a chunk of the received scientific data files, And a merge processing unit for merging with the chunk.

 Advantageously, the mass scientific data instant analysis device may comprise a storage for storing the queried scientific data files according to the original data loading scheme of the database.

 According to the present invention, it is possible to provide a method for instantly analyzing large-capacity scientific data files.

 According to the present invention, it is possible to provide a method of directly analyzing and processing a query on a large scale scientific data file without data loading process.

 According to the present invention, it is possible to provide a method of directly analyzing large-capacity multi-dimensional scientific data files on a file without performing a data loading process, and distributing and / or parallelly processing queries.

According to the present invention, it is possible to provide a method of effectively performing parallel query processing in a large-scale scientific data file composed of a multi-dimensional array in a distributed environment.

 According to the present invention, it is possible to provide a method of omitting a data loading process and directly performing a distributed parallel processing of a query word on multidimensional array data on a file.

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.
1 is a diagram illustrating a method for instantly analyzing mass scientific data according to an embodiment of the present invention.
2 is a diagram illustrating a data loading process according to an embodiment of the present invention.
3 is a diagram illustrating a query processing plan in a multi-dimensional array DBMS according to an embodiment of the present invention.
FIG. 4 is a diagram illustrating a data processing process of the large scale scientific data instant analysis apparatus according to an embodiment of the present invention.
5 is a block diagram illustrating an in-situ scan operation unit according to an exemplary embodiment of the present invention.
6 is a flowchart illustrating a process of a local map processing unit according to an embodiment of the present invention.
7 is a flowchart illustrating a process of a Global Map processing unit according to an embodiment of the present invention.
FIG. 8 is a diagram illustrating a method for instantly analyzing mass scientific data according to an embodiment of the present invention.
FIG. 9 is a diagram showing a configuration of a large capacity scientific data instant analysis apparatus according to an embodiment of the present invention.

 Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings and accompanying drawings, but the present invention is not limited to or limited by the embodiments.

 As used herein, terms used in the present invention are selected from general terms that are widely used in the present invention while taking into account the functions of the present invention, but these may vary depending on the intention or custom of a person skilled in the art or the emergence of new technologies. In addition, in certain cases, there may be a term arbitrarily selected by the applicant, in which case the meaning thereof will be described in the description of the corresponding invention. Therefore, it is intended that the terminology used herein should be interpreted based on the meaning of the term rather than on the name of the term, and on the entire contents of the specification.

 1 is a diagram illustrating a method for instantly analyzing mass scientific data according to an embodiment of the present invention.

 The large scale scientific data instant analysis apparatus according to an embodiment of the present invention can directly analyze and / or query on a file without loading data on large scientific data files. The large capacity scientific data instant analysis apparatus according to an embodiment of the present invention can process a query through correspondence between an internal data structure of a scientific data file and an internal structure assuming a situation when loading the database. The mass scientific data instant analysis apparatus according to an embodiment of the present invention can process the query immediately in a distributed environment for multidimensional array data.

 Previously, scientific data was archived and distributed as one file along with metadata providing information about the experiment. To analyze the data, the corresponding file should be read and loaded into the DB, but it takes a very long time to load . Accordingly, there is a problem that the total time from the actual file acquisition time to the completion of the query processing using the DB is very long. Furthermore, analysis queries on scientific data are not frequent, so existing DBs designed to assume frequent queries after loading are not suitable. The large capacity scientific data instant analysis apparatus according to an embodiment of the present invention can solve the above problems.

 The large scale scientific data instant analysis apparatus according to an embodiment of the present invention can directly analyze and query large scale scientific data files on a file without loading data.

 The large scale scientific data instant analysis apparatus according to an embodiment of the present invention can process a query of a multidimensional array directly on a file without loading the data into a DBMS. First, the large scale scientific data instant analysis device can match the internal data structure of the scientific data file and the internal data structure in the DB when the corresponding file is loaded in the DB. Second, it is possible to distribute the files according to the partition arrangement of the DB internal data structure in the distributed environment. Third, input / output performance can be improved by filtering in the file scan process for query processing. Fourth, we can provide a query processing flow and structure to enable direct query processing on scientific data files.

 The large capacity scientific data instant analysis apparatus according to an embodiment of the present invention can directly analyze large scale multidimensional scientific data files on a file without performing data loading and distribute and / or parallelize queries.

In particular, the large capacity scientific data instant analysis apparatus according to an embodiment of the present invention provides a correspondence between an internal data structure of a large-capacity multi-dimensional scientific data file and a DB internal data structure assuming a situation when loading the data file into a DB, The distributed query processing for multidimensional data can be performed immediately without using the file. Furthermore, the DB internal data structure is stored in the DB immediately afterwards, so that it is possible to effectively cope with subsequent iterative queries.

 2 is a diagram illustrating a data loading process according to an embodiment of the present invention.

 According to one embodiment of the present invention, scientific data contains observations or observation results of various phenomena of the real world, and often has a multi-dimensional array. For example, the satellite photographed image information is information in which an image value photographed at a specific position at a specific time is recorded. That is, the image information for a cell on a three-dimensional (latitude, longitude, and time) basis is composed of RGB values. Such a multidimensional array structure is difficult to support efficient storage and retrieval with existing relational DBMSs that store data in a two-dimensional table format. As a result, a multi-dimensional array DBMS for efficiently storing multi-dimensional arrays has appeared. A typical example is SciDB. In order to effectively support large-scale multidimensional arrays, a multidimensional array DBMS divides the array into chunks and distributes them to each node in the cluster to parallelize the input (input) and output (output) Improves performance. Scientific data, on the other hand, is created in a way that contains both experimental data and metadata in a single file format for ease of maintenance and distribution. Representative scientific data file formats include HDF5 and NetCDF.

 Referring to this drawing, a data loading process is performed in order to load a scientific data file into a multi-dimensional array DBMS. In the data loading process, the data is read and the data is reconstructed in a multidimensional array. In this step, an intermediate file to a one-dimensional array of a multidimensional array, a distribution step of one-dimensional data, a loading step of divided one-dimensional data, a reconstruction of a one- step).

 According to an embodiment of the present invention, loading of such a scientific data file into a multi-dimensional array DBMS takes a lot of time until completion of loading due to various processes as described above. As a result, the total time taken to process analytical queries after obtaining the actual scientific data file takes a long time due to the data loading time. Scientific data does not frequently query the generated data due to its nature. Accordingly, a lot of time and resources are wasted in the process of loading data that is not frequently processed in the DB.

 According to an embodiment of the present invention, a scientific data file format such as HDF, netCDF supports file unit management and distribution of scientific data. However, the scientific data file format does not provide a standardized query language and advanced processing functions such as the SQL query language provided by DBMS, but only file format definition and API.

According to one embodiment of the present invention, the scientific data created and / or distributed in the scientific data file format is so large that one file is several hundred gigabytes. When processing such large files on a single system with per-file APIs, the processing performance is not scalable due to input / output (I / O) and computing constraints on a single node.

 3 is a diagram illustrating a query processing plan in a multi-dimensional array DBMS according to an embodiment of the present invention.

 The external file technique according to an embodiment of the present invention can provide a method of directly querying a RAW file in a relational SQL query language without a data loading process. A representative example of this technique is Oracle's external table. The external table method is a method of making data in a comma-separated values (CSV) format outside the DB appear to be in the DB so that the file data can be used in the DB.

 However, the external file technology does not provide advanced DB functions such as DML, index, statistical information, etc., and can perform a simple query on the source file. In addition, an embodiment of the present invention relating to high-speed query processing of a scientific data file modeled as a multidimensional data model in a distributed parallel environment in that it provides a correspondence between a DB table modeled as a relational data model on a single node and a file such as CSV This is different from the large-scale scientific data instantaneous analysis device according to

 The in-situ query processing technique according to another embodiment of the present invention is the same as the external file in that the query processing is performed without loading the database to a raw file. Instead, in-situ query processing techniques are used to improve performance: first, indexing to reduce parsing costs; second, skip read operations through filtering pushdown; third, parallel processing of data using multiple threads; And incremental loading into the DB. As a representative example of the in-situ query processing technique, there are NoDB, SCANRAW, and the like. However, since the In-Situ query processing technology targets relational data of a 2D table format on a single node, it is an embodiment of the present invention relating to a high-speed query processing of a scientific data file modeled as a multidimensional data model in a distributed parallel environment This is different from the large-scale scientific data instantaneous analysis device according to

 SDS / Q according to an embodiment of the present invention is a distributed parallel system in which in-situ analysis is applied to HDF5 data, which is one of scientific data formats. The system was implemented in a supercomputer environment with a parallel file system with large memory. SDS / Q improves performance by placing large-capacity HDF5 files in a parallel file system and using in-memory indexes for in-file data to perform in-memory data processing. This system is similar to the large capacity scientific data instant analysis apparatus according to an embodiment of the present invention in that it supports immediate query processing on scientific experiment data files in a distributed parallel structure, but provides a modeling and query language for multidimensional arrays It differs from the large capacity scientific data instant analysis apparatus according to the embodiment of the present invention.

 The large scale scientific data instant analysis apparatus according to an embodiment of the present invention aims at enabling immediate query processing using large scale scientific data files modeled in a multidimensional array without using a DB loading process. In particular, it provides a standardized multidimensional array query language for scientific data that is modeled as a multi-dimensional array model and archived as one file, and supports distributed parallel processing of analysis queries written in the corresponding language, And to enable standardized high-speed analysis query processing.

 The large scale scientific data instant analysis apparatus according to an embodiment of the present invention can provide a method of efficiently processing a parallel scientific query in a distributed environment with large capacity scientific data files constituted by a multidimensional array. In addition, the data loading process can be omitted, and the query words for the multidimensional array data can be directly subjected to distributed parallel processing on the file.

 According to the large capacity scientific data instant analysis apparatus according to an embodiment of the present invention, all the existing multi-dimensional array query operations can be applied without data loading process, and the data in the corresponding file is corresponded to the internal structure of the existing multi- And then stored and / or managed as a DB.

 As a result of experimenting with actual scientific data files, the large-capacity scientific data instant analysis apparatus according to an embodiment of the present invention has a maximum of 75 (n = 75) compared with a load-to- We have confirmed that the performance improvement is more than double, and that the larger the size of the scientific data file, the larger the improvement in performance.

 The large scale scientific data instant analysis apparatus according to an embodiment of the present invention is configured to change data loading and query processing parts based on SciDB, which is a distributed DBMS storing a multidimensional array model. This is a design method that can be applied to other DBMSs and information systems that use existing multidimensional array models as storage units.

 This drawing shows a query processing plan in a conventional multi-dimensional array DBMS and a query processing plan according to an embodiment of the present invention. In the original query processing plan in the existing DBMS, the query processing is performed by scanning the array data structure stored in the database and creating a partial array. On the other hand, the large-capacity scientific data instant analysis apparatus according to an embodiment of the present invention changes the corresponding scan operator to an in-situ scan operator so that a scientific data file such as an HDF It is possible to change the query process so that the query is directly scanned.

 FIG. 4 is a diagram illustrating a data processing process of the large scale scientific data instant analysis apparatus according to an embodiment of the present invention.

 The mass scientific data instant analysis apparatus according to an embodiment of the present invention includes an HDP merger and / or an in-situ scan operation unit to perform immediate query processing while directly scanning data from a scientific data file . The file merge unit (HDP merger) can merge HDF science data files into as many files as the number of nodes where the DB instance is located. According to an embodiment of the present invention, the file merge unit may process data files in formats other than the HDF file format. The in-situ scan operation unit can scan a file directly from the HDF files using an in-situ scan operator. The in-situ scan operation unit according to an exemplary embodiment of the present invention may include a local map processing unit, a global map processing unit, and / or a query processing unit. The local map processor can construct a multidimensional array on memory in units of nodes from the input HDF files. The global map processing unit can construct a multi-dimensional array structure of each node unit created in the local map processing unit logically as one large array. The query processor can perform query processing such as subarray and output the final result array.

 This drawing shows a data processing process of the large capacity scientific data instant analysis apparatus according to an embodiment of the present invention which enables immediate query processing on scientific data files in HDF format.

 The file merger (HDF merger) can merge HDF, which is a number of scientific data formats, by the number of SciDB instances. The merged RAW files can be distributed to DB Instances. Subsequently, when a user submits a query to SciDB to analyze the scientific data, an in-situ scan operation can be performed to read the RAW file. Details of the in-situ scan operation unit will be described later.

 5 is a block diagram illustrating an in-situ scan operation unit according to an exemplary embodiment of the present invention.

 According to one embodiment of the present invention, in a distributed multidimensional array DBMS, one large multidimensional array structure can be divided into several tens to thousands of chunks in units of chunks and can be distributedly arranged for each node. At this time, the arrangement of the chunks can be performed through hashing. The large capacity scientific data instant analysis apparatus according to an embodiment of the present invention can perform local mapping and global mapping, which are two-step mapping processes, in order to associate a file with a multi-dimensional array arrangement structure.

 The in-situ scan operation unit according to an exemplary embodiment of the present invention may include a local map processing unit and / or a global map processing unit. The Local Map processing unit according to an embodiment of the present invention may include a filtering processing unit, a READ processing unit, and / or a building processing unit. The global map processing unit according to an embodiment of the present invention may include a scatter processing unit, a gather processing unit, and / or a merge processing unit. A detailed description of each of the above-described configurations will be given later in the drawings.

 6 is a flowchart illustrating a process of a local map processing unit according to an embodiment of the present invention.

 The local map processing unit according to an embodiment of the present invention can read an HDF file and create a partial memory array structure. Referring to this figure, a local map processing unit according to an embodiment of the present invention may include a filtering processing unit, a read processing unit, and / or a building processing unit.

According to one embodiment of the present invention, one of the frequently used query types when analyzing Array data is to search and analyze data of a part of the entire array data. The large scale scientific data instant analysis apparatus according to an embodiment of the present invention performs a filtering process of a local map to determine data necessary for a query so that only the corresponding data required for a query can be read and analyzed in a raw science data file can do.

 The filtering processor can search the query plan generated by the multidimensional array DBMS to find the filtering operator that retrieves the partial data of the array. When querying only an optional area other than all data, the filtering section may transmit the filtering information to the leading processing section so that the area not selected from the input step is not transmitted to the upper operators.

 According to one embodiment of the present invention, the leading processing unit and the building processing unit are the most basic configuration of the in-situ analysis method.

 The leading processing unit can read the scientific data from the RAW file. At this time, only necessary data can be read by using the filtering information received from the filtering processing unit. According to an embodiment of the present invention, the size of a unit for reading scientific data may be the size of an array chunk used in a DBMS. The mass scientific data instant analysis apparatus according to an embodiment of the present invention may further include a configuration (data arrangement unit) for arranging data when the unit for reading data is not a chunk size but sequentially reading the data. According to an embodiment of the present invention, in a distributed multidimensional array DBMS, multidimensional array data is divided into chunks and stored, and data is stored in order of dimensions defined in the array schema in each chunk. Therefore, if the data sorting unit according to an embodiment of the present invention does not read in units of chunks but maps to arrays of SciDBs, it is possible to change data according to a policy for storing SciDB data, You can perform sorting based on my position.

 The building processing unit can perform a role of mapping chunks of scientific data read by the leading processing unit into an array structure in the DB. The building processor according to an embodiment of the present invention can obtain the chunk Id and the position information in the chunk using the coordinates of the data read for the mapping. Then, mapping can be performed to a specific chunk of the array data structure in the actual DB using the read scientific data, position and / or chunk Id. The reading and building process of the Local Map processor according to an embodiment of the present invention ends after completing the mapping of the data required for the query to the SciDB array.

 7 is a flowchart illustrating a process of a Global Map processing unit according to an embodiment of the present invention.

 According to an embodiment of the present invention, local arrangement chunks generated by DB Instances through a Local Map process are rearranged according to an array placement policy to be created and / or located when data is loaded in an original multi-dimensional array DBMS Global Map process can be performed.

 This drawing shows a process in which the Global Map processing unit rearranges local arrays created by DB instances of respective nodes. The global map processing unit according to an embodiment of the present invention may include a scatter processing unit, a gather processing unit, and / or a merge processing unit.

 According to an embodiment of the present invention, arrays created on each instance after the Local Map process can be transmitted to DB Instances matching the original array chunk partitioning policy through the network. This transmission process may be performed by a Scatter processing unit and / or a Gather processing unit of the Global Map. The skater processing part can transmit data to other instances. The receiver processing unit can receive the transmitted data. When the received data belongs to the same array chunk, the merge processing unit can merge the received data into one array chunk. According to an embodiment of the present invention, the merged result SciDB array can be transmitted to an upper operator on the query processing plan of the in-situ scan operation unit.

 FIG. 8 is a diagram illustrating a method for instantly analyzing mass scientific data according to an embodiment of the present invention.

 The mass scientific data instant analysis method according to an embodiment of the present invention includes merging scientific data files according to the number of nodes where an instance of a database is located (step 8010), arranging the merged science data files in an array structure in the database A step 8020 of relocating the placed scientific data files according to the original data loading method of the database, and / or a querying step 8040 of querying the relocated scientific data files .

According to another embodiment of the present invention, the merging step merges a plurality of scientific data files having the same structure by the number of nodes, and merges the same into scientific data files of a larger size, The size of one of the data files may not exceed the available memory size of the node.

 According to another embodiment of the present invention, the step of arranging includes filtering the merged scientific data files so as to process only scientific data that is a direct object of the query, not all of the data, And / or generating a multidimensional array on the memory on a per-node basis with the read-processed scientific data files.

 According to another embodiment of the present invention, the step of generating the multidimensional array may include the step of generating the multidimensional array by using the chunk identification information of the read scientific data files and the location information in the chunks, To specific chunks in the database.

According to another embodiment of the present invention, the rearranging step may include rearranging the scientific data to be located in another node according to the original data loading method of the database among the chunks of the scientific data files disposed in the memory of each of the nodes, Transferring the chunks of the received scientific data files to another node, receiving chunks of the scientific data files to be located at the other node, and / or transmitting chunks of the received scientific data files to the chunks of already placed scientific data files And merging.

 According to another embodiment of the present invention, the mass scientific data immediate analysis method may include storing the queried scientific data files according to an original data loading method of the database.

 FIG. 9 is a diagram showing a configuration of a large capacity scientific data instant analysis apparatus according to an embodiment of the present invention.

 The large capacity scientific data instant analysis apparatus 9050 according to an embodiment of the present invention includes a file merge unit 9010 for merging scientific data files according to the number of nodes where instances of a database are located, A global map processing unit 9030 for rearranging the arranged scientific data files according to the original data loading method of the database and / And a query processing unit 9040 for querying the submitted scientific data files. The file merger can convert large-scale scientific data files into larger files according to the number of nodes. The local map processing unit reads each merged science data file and constructs a multidimensional array on the memory for each scientific data file for each node through a local map process. The global map processing unit can map the multidimensional arrays of the nodes generated through the local map processing unit to the array chunks to be distributed in accordance with the original array chunk partitioning method when the data is loaded in the DBMS. The query processing unit can process the query through the global map processing unit on the array chunks arranged in the same manner as in the existing data loading process.

 According to another embodiment of the present invention, the file merge unit merges a plurality of scientific data files having the same structure by the number of nodes, and merges the same into scientific data files of a larger size, The size of one of the files may not exceed the available memory size of the node. The file merging unit may merge the scientific experiment data files having a plurality of the same structure by the number of the computing nodes constituting the cluster to output data files of a larger size.

According to another embodiment of the present invention, the local map processing unit may include a filtering processing unit for filtering the merged scientific data files so as to process only scientific data, which is a direct object of a query, And / or a building processor for generating a multi-dimensional array on the memory in units of the nodes on the basis of the read-processed scientific data files. The local map processing unit can operate only on each computing node in the cluster. The local map processing unit may include a filtering processing unit for generating the corresponding information so that only the range value of the partial array and the cell value in the array can be directly selected for the merged science experiment data file acquired from the file merge unit have. The local map processing unit may include a leading processing unit for reading only the direct object data of the query from the file through the filtering step. The local map processing unit may include a building processing unit for generating a multidimensional array on the memory in units of nodes with the read scientific experiment data.

 According to another embodiment of the present invention, the building processing unit uses the chunk identification information of the read-processed scientific data files and the location information in the chunks to store the read scientific data files in the database It can be placed in a specific chunk. The building processing unit calculates the arrangement chunks and the positions in the chunks in which the corresponding cells are to be located in the array within the array by receiving data received through a reading processing unit that reads only the direct object data of the query directly from the file through the filtering processing unit, You can convert to an array chunk. The building processor can generate an array chunk on the memory according to a method of distributing one multidimensional array to chunks in an existing distributed multidimensional array DBMS.

 According to another embodiment of the present invention, the global map processing unit may include a chunk of the scientific data files arranged in the memory of each of the nodes, A gather processing unit for receiving chunks of scientific data files to be located at the other nodes, and / or a chunk of the received scientific data files, And a merge processing unit for merging with the chunks of the placed scientific data files. The global map processing unit may include a skater processing unit for transferring the partial areas in the array to be located at different nodes to other nodes according to the original arrangement chunk arrangement method among the in-memory arrangement chunks of each node. The global map processing unit may include a handler processing unit that receives the arrangement areas to be managed by the other nodes from among the partial arrangement areas transmitted from the skater processing unit. The global map processing unit may include a merge processing unit that has subarray regions received from the plurality of nodes received by the header processing unit and merges the nodes with the array chunks of the subarray regions.

 According to another embodiment of the present invention, the mass scientific data instant analysis apparatus may include a storage unit for storing the queried scientific data files according to the original data loading method of the database. The merge processing unit may merge the subsequence regions received from other nodes with the array chunks of the subsequence regions. The merge processing unit may cause the arrangement chunks to be generated and / or arranged in the memory in the same manner as the arrangement of the arrangement chunks in the multi-dimensional arrangement DBMS finally. At this time, if the size of the array chunk exceeds the available memory, it can be actualized on the disk. Furthermore, the mass scientific data instant analysis device can physically store the in-memory array chunks into the storage structure of the actual DB after the completion of the query process, if necessary.

 A module, unit or block in accordance with embodiments of the present invention may be a processor / hardware that executes sequential execution processes stored in a memory (or storage unit). Each step or method described in the above embodiments may be performed by hardware / processors. Further, the methods proposed by the present invention can be executed as codes. This code may be written to a storage medium readable by the processor and thus readable by a processor provided by an apparatus according to embodiments of the present invention.

 Although the drawings have been described for the sake of convenience of explanation, it is also possible to design a new embodiment by incorporating the embodiments described in each drawing. It is also within the scope of the present invention to design a computer-readable recording medium in which a program for executing the previously described embodiments is recorded according to the needs of those skilled in the art.

 The apparatus and method according to the present invention are not limited to the configuration and method of the embodiments described above as described above, but the embodiments described above may be modified so that all or some of the embodiments are selectively And may be configured in combination.

 Meanwhile, the image processing method of the present invention can be implemented as a code that can be read by a processor on a recording medium readable by a processor included in a network device. The processor-readable recording medium includes all kinds of recording apparatuses in which data that can be read by the processor is stored. Examples of the recording medium on which the processor can read are ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like. In addition, the processor-readable recording medium may be distributed over network-connected computer systems so that code readable by the processor in a distributed fashion can be stored and executed.

 While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the present invention.

 In this specification, both the invention of the invention and the invention of the method are explained, and the description of both inventions can be supplemented as necessary.

9010: File merge unit
9020: Local map processor
9030: Global map processor
9040:
9050: Large scale scientific data instant analysis device

Claims (5)

A file merge unit for merging scientific data files according to the number of nodes where an instance of the database is located;
A local map processing unit for arranging the merged scientific data files in an array structure in the database;
A global map processing unit for rearranging the arranged scientific data files according to an original data loading method of the database; And
A query processor for querying the relocated scientific data files;
Lt; / RTI >
Wherein the global map processing unit includes a merging processing unit for arranging and / or arranging the arrangement chunks in a memory in the same manner as the arrangement of the arrangement chunks in the multidimensional arrangement database management system (DBMS)
The file merge unit merges a plurality of scientific data files having the same structure by the number of nodes, merges the same into larger sized scientific data files,
Wherein the size of one of the merged science data files does not exceed the size of available memory of the node. delete Merging scientific data files according to the number of nodes in which instances of the database are located;
Arranging the merged science data files into an array structure in the database;
Rearranging the placed scientific data files according to an original data loading method of the database; And
Querying the relocated scientific data files;
Lt; / RTI >
Wherein the relocating comprises creating and / or placing arrangement chunks on a memory in the same manner as the arrangement chunks are arranged in a multi-dimensional array database management system (DBMS)
The merging step merges the plurality of scientific data files having the same structure by the number of the nodes to merge them into larger sized scientific data files,
Wherein the size of one of the merged science data files does not exceed the size of available memory of the node. delete  Merging the scientific data files according to the number of nodes in which the instances of the database are located, arranging the merged science data files in an array structure in the database, rearranging the arranged science data files according to the original data loading method of the database And the file merge unit merges the plurality of scientific data files having the same structure by the number of the nodes to merge them into the larger size scientific data files, Wherein the size of one of the scientific data files is not greater than the available memory size of the node.

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