Symantec Interview Question for Associates


Country: India
Interview Type: In-Person




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1
of 1 vote

i guess using Hash methods 'll be more effiicient than Binary search (if database already stored with hash values)

- smilelearner September 18, 2012 | Flag Reply
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0
of 0 votes

That's the answer I was looking for, HASHING!! But, how hashing is achieved in case of millions of rows?

- kaustubh deshmukh September 18, 2012 | Flag
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0
of 0 votes

In java, you can just create Hashmap or ( Tree Hashmap [sorted : so more efficient] ). you can give a key in it and values associated with it. for generating a key you can create your own hash methods, or use standard hash function like "MD5" store those Values with its key. so to search it, we can compute its hash value and getValue(Key) somewhat like O(1) search and thats it .

- smilelearner September 18, 2012 | Flag
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0
of 0 votes

Caching rather than hashing

- Ashupriya September 25, 2012 | Flag
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0
of 0 vote

i think indexing using hash values is better

- krishnam6767 September 19, 2012 | Flag Reply
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1
of 1 vote

sample code for indexing?

- smilelearner September 20, 2012 | Flag
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0
of 0 vote

Search Efficiently :
Depends on what job position you are looking for, you might want to answer it from a different aspect. But I think this question is asking you methods or different factors can effect the search.
1. Definitely "Hash " is a good answer.
2. (building) Indexes , in data warehouse, bitmap index may apply on some columns like gender or something ( since you dont really do transaction in data warehouse, so bitmap works here, not in transaction tables)
3. Table Partitions
4. parallel operations ( well, depends on if the DBA allows you to sacrifice some server performance to increase your efficiency)

- Zhijing April 03, 2013 | Flag Reply
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0
of 0 vote

We can use hashing for equality searching and b-trees or binary searches for range searches.

- Mz July 15, 2013 | Flag Reply
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-2
of 2 vote

By Using efficient search mechanisms like binary search....

- Narayana September 18, 2012 | Flag Reply


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