clustering try inserting more items into the hash table in the hash workshop applet as it gets more fullthe clusters grow larger clustering can result in very long probe lengths this means that accessing cells at the end of the sequence is very slow the more full the array isthe worse clustering becomes it' not usually problem when the array is half fulland still not too bad when it' two-thirds full beyond thishoweverperformance degrades seriously as the clusters grow larger and larger for this reason it' critical when designing hash table to ensure that it never becomes more than halfor at the most two-thirdsfull (we'll discuss the mathematical relationship between how full the hash table is and probe lengths at the end of this java code for linear probe hash table it' not hard to create methods to handle searchinsertionand deletion with linear probe hash tables we'll show the java code for these methods and then complete hash java program that puts them in context the find(method the find(method first calls hashfunc(to hash the search key to obtain the index number hashval the hashfunc(method applies the operator to the search key and the array sizeas we've seen before nextin while conditionfind(checks whether the item at this index is empty (nullif notit checks whether the item contains the search key if the item does contain the keyfind(returns the item if it doesn'tfind(increments hashval and goes back to the top of the while loop to check whether the next cell is occupied here' the code for find()public dataitem find(int key/(assumes table not fullint hashval hashfunc(key)/find item with key /hash the key while(hasharray[hashval!null/until empty cell/found the keyif(hasharray[hashvalgetkey(=keyreturn hasharray[hashval]/yesreturn item ++hashval/go to next cell hashval %arraysize/wrap around if necessary return null/can' find item