Examples of using Hash table in English and their translations into Hungarian
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Colloquial
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Official
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Medicine
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Ecclesiastic
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Financial
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Programming
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Official/political
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Computer
OK, so hash tables.
That's kind of like a hash table.
Your hash table you think.
Creating a Hash Table.
So hash tables are really just buckets.
AUDIENCE: So hash table.
A hash table is a hash function.
That means your hash table.
Between hash tables and tries.
Choice of tries or hash tables.
Between a hash table and a try.
How could you do that with a hash table index?
I really like hash tables. They're pretty cool.
You will have your choice between hash tables and tries.
AUDIENCE: So hash table has a predetermined size, like a[INAUDIBLE] of buckets?
I really like hash tables.
A hash table is merely an implementation detail and not the only possible approach.
So in your pset, you have your choice of tries or hash tables.
But if you choose a try or hash table, as long as it works, we're happy with that.
OK we're going to go into tries,which are a little crazy. I like hash tables.
A hash table is an unordered data structure and there are many types of queries which hash indexes cannot even help with.
So when you are sorting things by like the first letter of their name,that's kind of like a hash table.
Hash tables aren't sorted data structures, and there are a lot of forms of questions which hash indexes can not even help with.
The reason hash indexes are used is because hash tables are extremely efficient when it comes to just looking up values.
Since a hash table is basically an associative array, a typical entry would look something like“Abc=> 0x28939″, where 0x28939 is a reference to the table row where Abc is stored in memory.
A standard binary heap based priority queue does not directly support the operation of searching for one of its elements,but it can be augmented with a hash table that maps elements to their position in the heap, allowing this decrease-priority operation to be performed in logarithmic time.
But basically, all a hash table is a hash function that tells you which bucket to put each of your data, each of your elements in.
So this idea works if your hash table you think is much larger than your data set or if you want to try and minimize chaining until it's absolutely necessary.
Looking up a value like“Abc” in a hash table index and getting back a reference to the row in memory is obviously a lot faster than scanning the table to find all the rows with a value of“Abc” in the Employee_Name column.
