Abstract: Example aspects include techniques for anomaly detection via sparse judgmental samples. These techniques may include generating a qualified timestamp corresponding to execution of a first operation of a first transaction over a database and determining, based on the qualified timestamp, that a row of a table is not locked by a second operation of a second transaction over the database. In addition, the techniques may include determining that the row meets a condition of the first operation. Further, the techniques may include updating, based on the qualified timestamp, the row in response to the row meeting the condition, the updating including acquiring a lock on the row of the table.

Abstract: Example aspects include techniques for anomaly detection via sparse judgmental samples. These techniques may include generating a qualified timestamp corresponding to execution of a first operation of a first transaction over a database and determining, based on the qualified timestamp, that a row of a table is not locked by a second operation of a second transaction over the database. In addition, the techniques may include determining that the row meets a condition of the first operation. Further, the techniques may include updating, based on the qualified timestamp, the row in response to the row meeting the condition, the updating including acquiring a lock on the row of the table.

Abstract: Methods, systems, and computer program products are provided that construct and execute multi-step query plans in a database application. A database application accepts a query such as, for example, a graph query. The database application generates a physical query plan comprising a set of execution steps that perform the query. The set of execution steps comprises at least an initial step, an intermediate step and a final step. The database executes the query by passing control to the initial step that, when complete, passes execution control to some other step. The intermediate step executes and when complete, may pass execution control to any other step including itself. Steps may be configured to communicate arbitrary data between steps. The generated query plan may also comprise multiple multi-step sequences, and such sequences may be configured to execute in the alternative based on intermediate query results, or a parameter included in the query.

Abstract: Example aspects include techniques for anomaly detection via sparse judgmental samples. These techniques may include generating a qualified timestamp corresponding to execution of a first operation of a first transaction over a database and determining, based on the qualified timestamp, that a row of a table is not locked by a second operation of a second transaction over the database. In addition, the techniques may include determining that the row meets a condition of the first operation. Further, the techniques may include updating, based on the qualified timestamp, the row in response to the row meeting the condition, the updating including acquiring a lock on the row of the table.

Abstract: Methods, systems, and computer program products are provided that construct and execute multi-step query plans in a database application. A database application accepts a query such as, for example, a graph query. The database application generates a physical query plan comprising a set of execution steps that perform the query. The set of execution steps comprises at least an initial step, an intermediate step and a final step. The database executes the query by passing control to the initial step that, when complete, passes execution control to some other step. The intermediate step executes and when complete, may pass execution control to any other step including itself. Steps may be configured to communicate arbitrary data between steps. The generated query plan may also comprise multiple multi-step sequences, and such sequences may be configured to execute in the alternative based on intermediate query results, or a parameter included in the query.

Abstract: A computing device is provided, including non-volatile memory storing a database including a table having a plurality of rows. The computing device may further include a processor configured to receive a request to perform a first transaction on a row. The processor may assign a first transaction identifier (TID) of the first transaction to the row. The processor may impose a first exclusive TID lock on the first TID of the row and may impose a first exclusive data lock associated with the first transaction on the row. The processor may perform the first transaction on the row. Performing the first transaction may include modifying the table as stored in the memory. In response to completing the first transaction, the processor may release the first exclusive data lock on the row and release the first exclusive TID lock on the first TID of the row.

Abstract: A computing device is provided, including non-volatile memory storing a database including a table having a plurality of rows. The computing device may further include a processor configured to receive a request to perform a first transaction on a row. The processor may assign a first transaction identifier (TID) of the first transaction to the row. The processor may impose a first exclusive TID lock on the first TID of the row and may impose a first exclusive data lock associated with the first transaction on the row. The processor may perform the first transaction on the row. Performing the first transaction may include modifying the table as stored in the memory. In response to completing the first transaction, the processor may release the first exclusive data lock on the row and release the first exclusive TID lock on the first TID of the row.

Abstract: Methods, systems, apparatuses, and computer-readable storage mediums described herein are directed to dynamic memory allocation for query execution. A memory grant engine is configured to analyze query runtime execution statistics of instances of a query to detect whether memory allocation operations performed for the query in accordance with a first memory allocation policy (e.g., a last used grant-based policy) changes across executions of that query. Upon detecting such a pattern, the engine dynamically switches to utilizing a second memory allocation policy, such as a percentile-grant based policy. In accordance with such a policy, the engine determines an amount of memory space to be allocated for subsequent instances of the query based on an analysis of query runtime execution statistics of previous instances of the query. The determined amount of memory space is configured to satisfy a predetermined percentile value of the previous instances of the query.

Abstract: Examples described herein generally relate to executing a received graph database query. The received graph database query can be converted into a recursive common table expression (CTE). Multiple alternative processes for executing the recursive CTE can be generated based on the recursive CTE. A cost associated with each of the multiple alternative processes can be determined. One of the multiple alternative processes can be converted into a multi-step sequence based on the associated cost. The multi-step sequence can be executed on a database to retrieve a set of results in response to the received graph database query.

Abstract: An in-memory database system stores an entirety of a database within main memory of the computer system. The database includes a table comprising a plurality of rows including a particular row. A first transaction updating the particular row is executed to create a first version of the particular row. A second transaction updating the particular row is executed to create a second version of the particular row. The first version is visible only to the first transaction, and the second version is visible only to the second transaction. The in-memory database system may associate an index with the database table, the index referencing the plurality of rows, including referencing the first version of the particular row and the second version of the particular row. The in-memory database system may initiate garbage collection of the first version of the particular row and/or the second version of the particular row.

Abstract: A database system includes a query optimizer which applies transformations to a logical representation of an input query in a declarative query language to generate expressions for a query execution plan. The query optimizer stores information, for each rule application, indicating a transformation applied and bindings for the transformation, the bindings indicating expressions input to the transformation. When a new query execution plan is to be generated for the input query, the query optimizer uses this stored information, for expressions in an original query execution plan, to guide the query optimizer to produce a current query execution plan while avoiding transformations not used to generate expressions in the original query execution plan.

Abstract: Examples described herein generally relate to executing a received graph database query. The received graph database query can be converted into a recursive common table expression (CTE). Multiple alternative processes for executing the recursive CTE can be generated based on the recursive CTE. A cost associated with each of the multiple alternative processes can be determined. One of the multiple alternative processes can be converted into a multi-step sequence based on the associated cost. The multi-step sequence can be executed on a database to retrieve a set of results in response to the received graph database query.

Abstract: A database system includes a query optimizer which applies transformations to a logical representation of an input query in a declarative query language to generate expressions for a query execution plan. The query optimizer stores information, for each rule application, indicating a transformation applied and bindings for the transformation, the bindings indicating expressions input to the transformation. When a new query execution plan is to be generated for the input query, the query optimizer uses this stored information, for expressions in an original query execution plan, to guide the query optimizer to produce a current query execution plan while avoiding transformations not used to generate expressions in the original query execution plan.

Abstract: Methods, systems, and computer program products are provided that construct and execute multi-step query plans in a database application. A database application accepts a query such as, for example, a graph query. The database application generates a physical query plan comprising a set of execution steps that perform the query. The set of execution steps comprises at least an initial step, an intermediate step and a final step. The database executes the query by passing control to the initial step that, when complete, passes execution control to some other step. The intermediate step executes and when complete, may pass execution control to any other step including itself. Steps may be configured to communicate arbitrary data between steps. The generated query plan may also comprise multiple multi-step sequences, and such sequences may be configured to execute in the alternative based on intermediate query results, or a parameter included in the query.

Abstract: A data system in which a parent transaction that has multiple nested transactions has isolation between the nested transactions. Each of at least some of the plurality of operations are included within a nested transaction within the parent transaction. For each of at least some of the nested transactions, a begin transaction identifier is assigned to the nested transaction; and on or around completion of the nested transaction, a completion transaction identifier is assigned as a statement identifier at least one object version operated upon by the nested transaction. Visibility of a particular version of an object to an active nested transaction may be verified by comparing the begin transaction identifier of the active nested transaction to the statement identifier of the particular version of the object. The comparison is done such that visibility achieves the proper isolation between nested transactions.

Abstract: Running a transaction against a database that allows the transaction to be automatically retried when the transaction fails such that certain transaction failures that cause the transaction to be automatically retried are not visible to an entity that receives data as a result of the execution of the transaction. A first set of statements of a transaction is identified by identifying statements that will cause a change in the database state. A second set of statements is identified, that result in data being generated to be sent to the entity. The method further includes executing the first set of statements to change the database. The method further includes running the second set of statements separately from the first set of statements to generate data to be sent to the entity.

Abstract: An in-memory database system stores an entirety of a database within main memory of the computer system. The database includes a table comprising a plurality of rows including a particular row. A first transaction updating the particular row is executed to create a first version of the particular row. A second transaction updating the particular row is executed to create a second version of the particular row. The first version is visible only to the first transaction, and the second version is visible only to the second transaction. The in-memory database system may associate an index with the database table, the index referencing the plurality of rows, including referencing the first version of the particular row and the second version of the particular row. The in-memory database system may initiate garbage collection of the first version of the particular row and/or the second version of the particular row.

Abstract: An in-memory database system stores the entirety of a database that is being operated on by a database system within main memory. The database includes a table that comprises a plurality of rows including a particular row. The database table comprises a first version of the particular row having a first valid time, and a second version having a second valid time. Index(es) are associated with the database table. Each index references the plurality of rows, including referencing the first and second versions of the particular row. A transaction acting on the first version of the particular row is executed. The first version of the particular row is visible to the transaction based on the first valid time and the second version of the particular row being not visible to the transaction based on the second valid time.

Abstract: An in-memory database system stores the entirety of a database that is being operated on by a database system within main memory. The database includes a table that comprises a plurality of rows including a particular row. The database table comprises a first version of the particular row having a first valid time, and a second version having a second valid time. Index(es) are associated with the database table. Each index references the plurality of rows, including referencing the first and second versions of the particular row. A transaction acting on the first version of the particular row is executed. The first version of the particular row is visible to the transaction based on the first valid time and the second version of the particular row being not visible to the transaction based on the second valid time.

Abstract: A data system in which a parent transaction that has multiple nested transactions has isolation between the nested transactions. Each of at least some of the plurality of operations are included within a nested transaction within the parent transaction. For each of at least some of the nested transactions, a begin transaction identifier is assigned to the nested transaction; and on or around completion of the nested transaction, a completion transaction identifier is assigned as a statement identifier at least one object version operated upon by the nested transaction. Visibility of a particular version of an object to an active nested transaction may be verified by comparing the begin transaction identifier of the active nested transaction to the statement identifier of the particular version of the object. The comparison is done such that visibility achieves the proper isolation between nested transactions.