<prompt> Hlalosa hore na sefe ea Bloom ke engnan  <response>: Instruction in English: Explain what a Bloom filter is . Response in English: A Bloom filter is a probabilistic data structure that is used to test whether an element is a member of a set. It is designed to be space-efficient and fast, but it may return false positives, meaning it may indicate an element is present in the set even if its not. False negatives however are not possible, meaning if the filter indicates an element is not in the set, then its certainly not in the set. The Bloom filter works by representing the set as a bit array of length m, which is initially set to all zeroes. When an element is added to the set, it is mapped to k indices in the bit array using k different hash functions, and the bits at those indices are set to 1. To check if an element is in the set, the same k hash functions are used to compute its indices, and the element is considered to be in the set only if all the bits at those indices are 1.Due to its probabilistic nature and the possibility of false positives, a Bloom filter is not always the best choice for every use case. However, it can be useful in situations where false positives are acceptable and memory usage is a concern. . Response in Sesotho: Setlhopha sa Bloom ke sebopeho sa data sa probabilistic se sebelisetsoang ho lekola hore na elemente ke setho sa sete. E etselitsoe ho boloka sebaka hantle le ho potlaka, empa e ka khutlisa maikutlo a fosahetseng, ho bolelang hore e kanna ea bontša hore ho na le ntho e teng sehlopheng leha e le sieo. Leha ho le joalo, li-negatives tsa bohata ha li khonehe, ho bolelang hore haeba sesefe se bontša hore ntho e itseng ha se sete, ka sebele ha se sete. Setlhopha sa Bloom se sebetsa ka ho emela sete joalo ka bolelele ba limithara, boo qalong bo behiloeng ho linoto tsohle. Ha elemente e kenyeletsoa sehlopheng, e etsoa mapa oa k indices ka hara bit array ho sebelisoa k mesebetsi e fapaneng ea hash, me likotoana tsa li-indices tseo li behiloe ho 1. Ho hlahloba hore na element e teng ka hara sete, k hash e tšoanang. mesebetsi e sebelisetsoa ho bala li-indices tsa eona, me element e nkoa e le ka sete ha feela likaroloana tsohle ho li-indices tseo e le 1. Ka lebaka la tlhaho ea eona ea ho khoneha le monyetla oa ho ba le li-positives tsa bohata, Bloom filter hase kamehla e leng khetho e molemo ka ho fetisisa. bakeng sa tsebeliso e ngoe le e ngoe. Leha ho le joalo, e ka ba molemo maemong ao ho ona maikutlo a fosahetseng a amohelehang le tšebeliso ea memori e amehang. 