Creating common information structures using list's stored in data step hash objects
... mind a node is further defined as a particular group of information that is made up of an index “key” and the associated data that is accessed via the key. We will only consider lists that use a single key variable in our hash table structure. The data associated with a key will be simply called “n ...
... mind a node is further defined as a particular group of information that is made up of an index “key” and the associated data that is accessed via the key. We will only consider lists that use a single key variable in our hash table structure. The data associated with a key will be simply called “n ...
Performance Problems in ABAP Programs: How to Fix Them Werner Schwarz
... BELNR, and GJAHR) that specifies a value for the field BELNR (0000000001) and returns one record from the database. An ideal index for such a database selection would start with fields MANDT and BELNR. Suppose there is no such index, however. In this case, the table’s key index must be used,2 which ...
... BELNR, and GJAHR) that specifies a value for the field BELNR (0000000001) and returns one record from the database. An ideal index for such a database selection would start with fields MANDT and BELNR. Suppose there is no such index, however. In this case, the table’s key index must be used,2 which ...
Average-Case Analysis of Algorithms and Data Structures
... The symbolic method (SYMBOL) is often direct and has the advantage of characterizing the special functions that arise from the analysis of a natural class of related algorithms. The COMPLEX method provides powerful tools for direct asymptotics from generating functions. It has the intrinsic advantag ...
... The symbolic method (SYMBOL) is often direct and has the advantage of characterizing the special functions that arise from the analysis of a natural class of related algorithms. The COMPLEX method provides powerful tools for direct asymptotics from generating functions. It has the intrinsic advantag ...
Average-Case Analysis of Algorithms and Data Structures
... The symbolic method (SYMBOL) is often direct and has the advantage of characterizing the special functions that arise from the analysis of a natural class of related algorithms. The COMPLEX method provides powerful tools for direct asymptotics from generating functions. It has the intrinsic advantag ...
... The symbolic method (SYMBOL) is often direct and has the advantage of characterizing the special functions that arise from the analysis of a natural class of related algorithms. The COMPLEX method provides powerful tools for direct asymptotics from generating functions. It has the intrinsic advantag ...
KorthDB6_ch11
... Periodic reorganization of entire file is required. Advantage of B+-tree index files: automatically reorganizes itself with small local changes, in the face of insertions and deletions. Reorganization of entire file is not required to maintain performance. (Minor) disadvantage of B+-trees: ...
... Periodic reorganization of entire file is required. Advantage of B+-tree index files: automatically reorganizes itself with small local changes, in the face of insertions and deletions. Reorganization of entire file is not required to maintain performance. (Minor) disadvantage of B+-trees: ...
root parent child leaf node edge
... You can have binary trees that are approximately balanced, so that the depth is still , but might have a larger constant hidden in the big-oh. As an aside, a binary heap does not have an efficient search operation: Since nodes at the same level of the heap have no particular ordering r ...
... You can have binary trees that are approximately balanced, so that the depth is still , but might have a larger constant hidden in the big-oh. As an aside, a binary heap does not have an efficient search operation: Since nodes at the same level of the heap have no particular ordering r ...
Chapter 7: Relational Database Design
... Periodic reorganization of entire file is required. Advantage of B+-tree index files: automatically reorganizes itself with small, local, changes, in the face of insertions and deletions. Reorganization of entire file is not required to maintain ...
... Periodic reorganization of entire file is required. Advantage of B+-tree index files: automatically reorganizes itself with small, local, changes, in the face of insertions and deletions. Reorganization of entire file is not required to maintain ...
On A Generic Parallel Collection Framework - Infoscience
... that subset of the elements in the collection is operated on sequentially. After nishing with one task, the processor pops a task of its queue if it is nonempty. Since tasks are pushed to the queue, the last (smallest) task pushed will be the rst task popped. At any time the processor tries to pop ...
... that subset of the elements in the collection is operated on sequentially. After nishing with one task, the processor pops a task of its queue if it is nonempty. Since tasks are pushed to the queue, the last (smallest) task pushed will be the rst task popped. At any time the processor tries to pop ...
Chapter11. Skip Lists and Hashing
... constructor() of SkipList /* * create an empty skip list : 0(maxlevel) * largekey: used as key in tail node * all elements must have a smaller key than “largekey” * maxElements: largest no of elements to be stored in the dictionary * theProb: probability that element on one level is also on the nex ...
... constructor() of SkipList /* * create an empty skip list : 0(maxlevel) * largekey: used as key in tail node * all elements must have a smaller key than “largekey” * maxElements: largest no of elements to be stored in the dictionary * theProb: probability that element on one level is also on the nex ...
Chapter 11: Indexing and Hashing
... Search-keys in the subtree to which Pi points are ≤ Ki,, but not necessarily < Ki, To see why, suppose same search key value V is present in two leaf node Li and Li+1. Then in parent node Ki must be equal to V ...
... Search-keys in the subtree to which Pi points are ≤ Ki,, but not necessarily < Ki, To see why, suppose same search key value V is present in two leaf node Li and Li+1. Then in parent node Ki must be equal to V ...
Chapter 11: Indexing and Hashing
... Search-keys in the subtree to which Pi points are Ki,, but not necessarily < Ki, To see why, suppose same search key value V is present in two leaf node Li and Li+1. Then in parent node Ki must be equal to V ...
... Search-keys in the subtree to which Pi points are Ki,, but not necessarily < Ki, To see why, suppose same search key value V is present in two leaf node Li and Li+1. Then in parent node Ki must be equal to V ...
Document
... reasonably avoided when you are working with nonkey attributes. • For example, one of an EMPLOYEE table’s attributes is likely to be the EMP_INITIAL. • However, some employees do not have a middle initial. • Therefore, some of the EMP_INITIAL values may be null. • There may be situations in which a ...
... reasonably avoided when you are working with nonkey attributes. • For example, one of an EMPLOYEE table’s attributes is likely to be the EMP_INITIAL. • However, some employees do not have a middle initial. • Therefore, some of the EMP_INITIAL values may be null. • There may be situations in which a ...
Index Tuning
... – Worst case: 1 IO per bucket – NOT balanced as number of IOs to reach a record depends on the hash function and key distribution. ...
... – Worst case: 1 IO per bucket – NOT balanced as number of IOs to reach a record depends on the hash function and key distribution. ...
Transposing Relations: from Maybe Functions to Hash Tables than
... collective types other than the powerset [6, 10, 11]. In particular, one of these operators will be related with the technique of representing finite data collections by hash-tables, which are efficient data-structures well-known in computer science [21, 12]. Second, we want to stress on the usefuln ...
... collective types other than the powerset [6, 10, 11]. In particular, one of these operators will be related with the technique of representing finite data collections by hash-tables, which are efficient data-structures well-known in computer science [21, 12]. Second, we want to stress on the usefuln ...
Document
... for every search-key value, and a pointer to every record in the file. Frequently, one wants to find all the records whose values in a certain attribute (which is not the searchkey of the primary index) satisfy some condition. Example 1: In the account database stored sequentially by account num ...
... for every search-key value, and a pointer to every record in the file. Frequently, one wants to find all the records whose values in a certain attribute (which is not the searchkey of the primary index) satisfy some condition. Example 1: In the account database stored sequentially by account num ...
Indexing and Hashing
... structure if search-key does not form a primary key. ! If Li, Lj are leaf nodes and i < j, Li’s search-key values are less ...
... structure if search-key does not form a primary key. ! If Li, Lj are leaf nodes and i < j, Li’s search-key values are less ...
Hash table
In computing, a hash table (hash map) is a data structure used to implement an associative array, a structure that can map keys to values. A hash table uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found.Ideally, the hash function will assign each key to a unique bucket, but it is possible that two keys will generate an identical hash causing both keys to point to the same bucket. Instead, most hash table designs assume that hash collisions—different keys that are assigned by the hash function to the same bucket—will occur and must be accommodated in some way.In a well-dimensioned hash table, the average cost (number of instructions) for each lookup is independent of the number of elements stored in the table. Many hash table designs also allow arbitrary insertions and deletions of key-value pairs, at (amortized) constant average cost per operation.In many situations, hash tables turn out to be more efficient than search trees or any other table lookup structure. For this reason, they are widely used in many kinds of computer software, particularly for associative arrays, database indexing, caches, and sets.