Patent ID: 12189657

Corresponding numerals and symbols in the different figures generally refer to corresponding parts unless otherwise indicated. The figures are drawn to clearly illustrate the relevant aspects of the embodiments and are not necessarily drawn to scale.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The making and using of the presently preferred embodiments are discussed in detail below. It should be appreciated, however, that the present invention provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed are merely illustrative of specific ways to make and use the invention, and do not limit the scope of the invention.

System and method embodiments are provided herein for using different storage formats for a primary database (or primary for short) and its replicas in a DMR system. As such, the advantages of both formats can be combined with suitable design complexity and implementation. For instance, the primary and replica can be in RS and CS formats respectively, or in CS and RS formats respectively. A database server employing this scheme is able to support mixed query workloads for better performance. For example, a query can span to multiple processing nodes using the more suitable storage format to lower processing cost. The scheme also increases storage efficiency, for example as the CS format is known to have better storage efficiency than the RS format. The embodiments include the design and algorithms to enable synchronization between the primary and replica. Although the embodiments discuss CS and RS storage formats, the concepts herein can be extended to heaps, heap with indices, covered indices or other formats.

FIGS.1A-1Cshow examples of database replication architectures.FIG.1Ashows a non-cascaded replication architecture101where a primary database110is replicated independently or directly to one or more replicas120.FIG.1Bshows a cascaded replication architecture102, where the primary110is replicated to a first primary120, which in turn is replicated to a second primary120, and so forth.FIG.1Cshows a logical view of both architectures. Both architectures can be represented as a mapping (replication) between a pairing of the primary110and one or more replicas120, whether directly in a non-cascaded manner or through a cascade of replicas120. The primary and replica each hold a copy of a database.

FIG.2shows an example of a shared nothing (SN) database cluster200with pairs of primary210and replica220. The SN database cluster200is handled by applying any of the replication architectures above for each participating processing node212, and using distributed query processing. The nodes212are processing nodes, e.g., database servers, with CPU and memory. Each primary210and replica220is handled by a corresponding node212. In this example, the cluster200includes a first pair of Primary1 and Replica1, and a second pair of Primary2 and Replica2, each handled by a processing node212. The processing nodes212can be connected through a switch202or a network. Cross-node and cost-based query planning can be implemented in a query optimizer or a database engine. The query optimizer may be part of the database engine, which is a program for managing database data, e.g., including performing query data, write data, replicate data, and/or other functions. The data statistics can be collected and saved by the nodes212of each primary and replica. The data statistics of each primary are in different format than the data statistics of its replica. Therefore, the node212for each replica also reports its data statistics to the node212of its corresponding primary. The data statistics of each primary are also replicated to its replica. Thus, when there is a failover of a primary, its replica would have collected the primary's statistics during a previous replication, and vice versa.

An example query that can be processed in the SN database cluster200is as follows:

SELECT T2.v4, COUNT(*) FROM T1, T2ON T1.v1 = T2.v1 WHERE T1.v2 = 136 and T2.v3>27GROUP BY T2.v4;

Conventionally, a plan executing for the query uses either RS or CS formats as follows. For example, the plan in Row Store (RS) includes:

HashAgg (sum)GATHERHashAgg(count)HashJoin (T1.v1=T2.v1)IndexScan T1.v2 = 136RowTableScan T2.v3 > 27 + BF /* bloom filter */
For the Column store (CS), the plan includes:

HashAgg (sum)GATHERHashAgg(count)HashJoin (T1.v1=T2.v1)CStoreScan T1.v2=136)CStoreScan T2.v3>27 + BF /* bloom filter */

According to an embodiment herein, the plan is generated instead using both RS and CS formats for the primary and replica, as follows:

HashAgg (sum)GATHERHashAgg(count)HashJoin (T1.v1=T2.v1)IndexSCAN T1.v2 = 136REDISTRIBUTECStoreScan T2.v3 > 27 + BF

The SN cluster-distributed query processing supports a cross-node REDISTRIBUTE iterator function, which ships data trunks from one processing node212(or database210) to the other. The REDISTRIBUTE iterator needs to ship data from a replica (or primary) to the corresponding primary (or replica). This can be supported in the SN cluster database200.

Changes can be propagated from the primary to the corresponding replica(s) via synchronization. Existing RS replication technology can be leveraged to handle catalog table changes imposed by Data Definition Language (DDL), Data Control Language (DCL), and at least some Data Manipulation Language (DMLs), as both RS and CS can use a row format to save and coordinate the catalog data. The data changes that are addressed using RS replication involve one side in RS format (e.g., at the primary or replica) and the other side in CS format (e.g., at the replica or primary). The changes may include INSERT and DELETE operations, while the UPDATE operation can be deduced from those two.

According to an embodiment, to enable the synchronization of changes between the primary and replica(s) with RS format on one side and CS format on the other, the RS and CS rows are kept aligned by a sequence. The sequence is a unique number identifying a row, and is incremented by one per each next row. The sequence number does not need to be globally unique. It is sufficient for the sequence to be unique within a portion of the table or the database, such as a partition of the table and the database. The sequence is assigned and fixed at INSERT time. The DELETE operation does not affect or change the sequence number of rows. With the sequence approach, the CS and RS do not require extra key or storage to map each row between them. The same sequence identifying the row is kept in both formats.

In an embodiment, the RS format includes heap pages and an affiliated index structure comprising a set of pointers for the heap pages. A heap page is a file, for instance of a fixed length, comprising a sequence of rows (referred to as heap records). The sequence number of the first row in the heap page is recorded in the heap page header, as shown inFIG.3. The use of the sequence of the first row in each heap page and the affiliated index structure allows retrieving any row in the heap pages. The affiliated index structure can be a B+-tree, a hash index or any other suitable index type, where each entry in the index points to a heap page or a group of heap pages.

The affiliated index structure serves as a sequence map to locate the sequence numbers in the heap page headers. This accelerates locating a row (in heap pages) by its sequence number. When a heap page is retrieved (using the affiliated index structure) with its starting row sequence number, any subsequent row (heap record) in the same heap page can be retrieved, e.g., implicitly according to its order in the page. For example, for a page with a sequence number 3456, the first row is 3456, the second is 3457, and the third is 3458, and so on. The sequence map (the affiliated index structure) can use several bytes to record the starting row sequence number of each heap page.

FIG.4shows an embodiment of a sequence map and shows how the sequence map may grow in size upon inserting rows into a table. The sequence map is used to locate a heap page with a starting row sequence number. Initially, the map is set at an initial level (level 0). A first map page or entry (level 0-page 0) is added for a first group of a predetermined number of heap pages, for example first 2000 heap pages. The map page or entry includes the starting row sequence number of the first heap page in the group and a pointer to locate the heap pages. The map page can use about 4 bytes, for example, to record the starting row sequence number. When a next heap page in a next second group of 2000 heap pages is added, the map is upgraded to a first level (level 1) by adding a map page or entry (level 1-page 0) indicating the first level. Additionally, a new map page or entry (level 0-page 1) corresponding to the added next heap page in the next group is added to the map. This added map page or entry includes the starting row sequence number of the first heap page in the second group of 2000 heap pages and a pointer to locate the corresponding heap pages. The map can grow by adding similarly more level 0 pages (level 0-page 2, level 0-page 3, . . . ) for each next group of 2000 heap pages, until reaching a predetermined maximum number of groups allowed per level, such as 1000 groups (0 to 999) per level. As such, the level 1 can accommodate about 1000×2000 heap pages. The level 1-page 0 map page or entry includes pointers to all level 0 pages in the map. The level 1-page 0 map page can use about 8 bytes, for example, to record the starting row sequence number of each of the level 0 pages.

When a next heap page is added beyond that maximum number of heap pages for level 1, the map is upgraded to a next level (level 2) by adding a map page or entry (level 2, page 0) indicating the next level. A next map page or entry (level 1 and page 1) is also added for the next added heap page. This map page or entry includes the starting row sequence number of the first heap page in the group beyond the 1000×2000 heap pages, and a pointer to locate the heap pages. The level 2-page 0 map page includes pointers to all level 0 and level 1 pages in the map. Following the same logic, the map can continue growing in pages and levels to accommodate more heap pages for more inserted rows.

In an embodiment, the CS format comprises a sequence of compression units (CUs), which each stores a fixed number (e.g., 100,000) of values or table entries, e.g., corresponding to the number of columns in a data table. Each CU has a CU descriptor persisted, for instance as metadata, in the RS and can share the same transactional protection in the RS. For example, if the RS uses multi-version concurrency control (MVCC), then MVCC is applied for the CU descriptor. Or, if the RS is lock based, then the stored CU descriptor is locked based. The CU descriptor includes a PointerToCU field pointing to its CU storage. The CU descriptor can include a DeletionBitmap field for flagging deleted rows where each bit represents a row in the CU. The DeletionBitmap field can be Run-Length Encoding (RLE) compressed. The CU descriptor can also include a NumberOfRows field indicating the number of rows in the CU. This value is fixed upon creating the CU.

To allow efficient compression (e.g., a better compression ratio) in the CS format, row ordering in the CS format may have higher priority to row ordering in the RS format. Therefore, the RS rows are ordered to match the ordering of the CS rows. In order to keep the sequence aligned for both formats, care should be taken that the INSERT and DELETE operations do not introduce sequence misalignment between the two formats.

In an example, the primary is stored in RS and the replica is stored in CS. The INSERT operation includes an insertion part and a scan part. The insertion part's function is to insert rows, and the scan part's function is to generate rows. A simple form of scan is reading from a comma-separated value (CSV) file or a foreign table. A more complex form of scan may involve joining with multiple tables. The query processor can generate the scan part by invoking query execution in both primary and replica.

An example query with the INSERT operation is as follows:

INSERT INTO U SELECT T2.v4, COUNT(*) FROM T1, T2ON T1.v1 = T2.v1 WHERE T1.v2 = 136 and T2.v3>27GROUP BY T2.v4;

The plan generated for the query is as follows:

INSERT (N)// insertion part. . .// plan below is scan partHashJoin (T1.v1=T2.v1)IndexSCAN T1.v2 = 136REDISTRIBUTECStoreScan T2.v3 > 27 + BF

The insertion part is thus generated by the query executor as follows:

/* Primary is RS and replica is CS */RS Insertion (INPUT: rows in raw format)1./* Loop to build CU first */for ( ;; )Compress the inputs into columnar format thus creating a CU;if (CU.size == 0) break;/* No current insert but delete/read is ok. Send the CU to replica. * /2.Set startSequence = global maintained insertion sequence;Ship <startSequence, #rows, CU> (referred to as shipment) to replica;3./* Concurrently, primary builds RS, and replica writes CU */Concurrently do:- In Primary: follows CU's row ordering, insert into RS. Wait for replica ACK;- In Replica: receive the shipment and insert into CS. Send ACK;4./* Error handling */If anything fails in the middle, abort the transaction.5./* Primary local commits and post-commits */When ACK is received, primary commits transaction locally.global maintained insertion sequence += #rows;

Further, the table of data processed above can be locked, e.g., prior to step 2, and released when the steps are completed. In another implementation, the CS and RS are put in a critical section which allows no concurrent insert operation but allows concurrent read or delete. For relatively small insertion, the lock down time is brief. For batch insertion, the RS format can utilize parallel insertion implementation to saturate system resource. Therefore, allowing parallel insertion is not needed. This insertion algorithm keeps the sequence aligned.

The DELETE operation can be treated similar to the INSERT operation. The DELETE operation includes a deletion part and a scan part. By executing the scan part of the deletion query, which may span both primary and replica, a list of sequences is to be deleted. For RS format, after identifying a qualified record, the heap page header is examined to obtain the sequence number. For CS, this is done by accumulating the CU descriptor's NumberOfRows field.

According to the RS format's MVCC rules, deleting a row is achieved by setting one or more flags in the record's header part without actually removing it from storage. In CS, deletion is done by setting the corresponding bit in the CU descriptor's DeletionBitmap field. The sequence is still maintained if in-place updates (which are updates that overwrite the target row in the same storage) are not performed. When the primary is CS and the replica is RS, the INSERT and DELETE operations are handled in a similar manner to the case of a primary RS and a replica CS described above. In the case of a primary CS and a replica RS, during INSERT, the primary node first builds the CS then ships the CS to the replica side in order to build the RS for the replica in alignment with the sequence at the CS.

FIG.5shows a flowchart of an embodiment of a method500for managing primary and replica databases using different storage formats. Specifically, a RS is used for the primary and a CS is used for the replica. The method500is implemented, e.g., by a database engine or DBMS, to establish a RS in the primary, and a CS in the replica. At step510, a plurality of columns in a table of data are compressed into a corresponding CU format suitable for the CS. The columns are obtained from a plurality of rows (e.g., consecutive rows) in the table. The rows are ordered in a format suitable for the CS, for instance to improve the compression ratio or efficiency in the CS. At step520, the same rows of the CU are inserted into a corresponding heap page (or file) in the RS. The rows in the RS are ordered in the same sequence of the rows inserted in the CU. At step530, the CU is inserted in the CS with a start sequence indicating the first row in the CU and the number of compressed rows. At step540, a CU descriptor is added to the CS with a pointer corresponding to the CU. The CU descriptor can be in RS format and points to the corresponding CU in the CS, and indicates the number of rows. The steps510to540are repeated until all the rows in the table are processed and added to the CS and RS. A similar method can be implemented using CS in the primary and RS in the replica. In this case, the RS can be added for the replica after committing the CS to the primary.

FIG.6is a block diagram of a processing system600that can be used to implement various embodiments including the methods above. For instance, the processing system600can be part of a DMR or database replication architecture as described above. In another scenario, the processing system600can be a computation node or a group of computation nodes, e.g., database servers, in the system. Specific devices may utilize all of the components shown, or only a subset of the components, and levels of integration may vary from device to device. Furthermore, a device may contain multiple instances of a component, such as multiple processing units, processors, memories, transmitters, receivers, etc. The processing system600may comprise a processing unit601equipped with one or more input/output devices, such as a speaker, microphone, mouse, touchscreen, keypad, keyboard, printer, display, and the like. The processing unit601may include a central processing unit (CPU)610, a memory620, a mass storage device630, a video adapter640, and an I/O interface660connected to a bus. The bus may be one or more of any type of several bus architectures including a memory bus or memory controller, a peripheral bus, a video bus, or the like.

The CPU610may comprise any type of electronic data processor. The memory620may comprise any type of system memory such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), read-only memory (ROM), a combination thereof, or the like. In an embodiment, the memory620may include ROM for use at boot-up, and DRAM for program and data storage for use while executing programs. In embodiments, the memory620is non-transitory. The mass storage device630may comprise any type of storage device configured to store data, programs, and other information and to make the data, programs, and other information accessible via the bus. The mass storage device630may comprise, for example, one or more of a solid state drive, hard disk drive, a magnetic disk drive, an optical disk drive, or the like.

The video adapter640and the I/O interface660provide interfaces to couple external input and output devices to the processing unit. As illustrated, examples of input and output devices include a display690coupled to the video adapter640and any combination of mouse/keyboard/printer670coupled to the I/O interface660. Other devices may be coupled to the processing unit601, and additional or fewer interface cards may be utilized. For example, a serial interface card (not shown) may be used to provide a serial interface for a printer.

The processing unit601also includes one or more network interfaces650, which may comprise wired links, such as an Ethernet cable or the like, and/or wireless links to access nodes or one or more networks680. The network interface650allows the processing unit601to communicate with remote units via the networks680. For example, the network interface650may provide wireless communication via one or more transmitters/transmit antennas and one or more receivers/receive antennas. In an embodiment, the processing unit601is coupled to a local-area network or a wide-area network for data processing and communications with remote devices, such as other processing units, the Internet, remote storage facilities, or the like.

While several embodiments have been provided in the present disclosure, it should be understood that the disclosed systems and methods might be embodied in many other specific forms without departing from the spirit or scope of the present disclosure. The present examples are to be considered as illustrative and not restrictive, and the intention is not to be limited to the details given herein. For example, the various elements or components may be combined or integrated in another system or certain features may be omitted, or not implemented.

In addition, techniques, systems, subsystems, and methods described and illustrated in the various embodiments as discrete or separate may be combined or integrated with other systems, modules, techniques, or methods without departing from the scope of the present disclosure. Other items shown or discussed as coupled or directly coupled or communicating with each other may be indirectly coupled or communicating through some interface, device, or intermediate component whether electrically, mechanically, or otherwise. Other examples of changes, substitutions, and alterations are ascertainable by one skilled in the art and could be made without departing from the spirit and scope disclosed herein.