Performance tuning for searching

Question

I am fairly new to DS and Algorithms and recently at a job interview I was asked a question on performance tuning along with code. We have a Data Structure which contains multi-billion entries and we need to search a particular word in that data structure. So which Java feature/library can we use to do the searching in the quickest time possible ?

On the spot I could not think of exact answer so I wrote that:

1. We can store the values in a map and search words in the map (but got stuck how to decide key-value pair in the map).

How can I understand the exact answer to this question and what can be the optimal solution(s) ?

Answer 1

After reading the question and getting clarification in the comments, I think what has become apparent to me is that: you needed to ask follow-up questions.

I'll try to break it down and provide comments that I hope will be helpful, because I also know what it's like to be "in the moment" and how nerves can stab you in the back when you least need them to.

We have a Data Structure which contains multi-billion entries and we need to search a particular word in that data structure.

I think a good follow-up question here would've been:

Q: What specific data structure is being used to contain all this data?

I would press until they give me an actual name and explain why it is not possible to name a Java algorithm/library. For all you know, the data structure could've been String[], a Set<String>, or even a fancy name for a file on disk (if they're trying to throw you off). They could've also clarified and said the DS was not relevant and that you could pick whichever DS you thought was best.

The wording also implies that they implemented the structure and that it's already populated in a system with, presumably, enough memory to hold all of it. Asking to confirm that this is really the case could've given you helpful information.

For example: "Based on the wording, it seems this mystery data structure is already implemented and fully populated in memory in a system with enough memory to hold it. Can you confirm my understanding here is correct? If not, could you clarify further?"

Given the suggested wording, and the fact that we don't have additional clarifications to go from, I will assume, for the purposes of this answer, that my suppositions are indeed correct.

Note that if you had been asked to design the data structure to hold all of this info, you would've had to ask very different questions, take memory constraints into account, and perhaps even ask about character sets/encodings (e.g. ASCII vs multi-byte Unicode).

Also, if you had been asked to design the search algorithm, then knowing the DS is a pre-requisite, and not knowing this could've made the task impossible. For example, the binary search algorithm implementation will look very different if you're working on an array vs a binary search tree, even though both would offer O(lg n) time complexity.

So which java feature/library can we use to do the searching in the quickest time possible?

Consistent with the 1st part, this question only asks what pre-existing/built-in Java code you would choose to perform the search for you. The "quickest time possible" here should make you think about solutions that are in O(1), i.e. are constant time. However, the data structure may open/close doors for you.

Some search algorithms in Java work on generics and others work on other types like arrays. Some algorithms work on Maps while others work on Lists, Sets, and so on. The follow-up question from the first part could've helped in answering this question.

That said, even if you knew the DS, but couldn't think of a specific method name or such at the time, I also think it should be considered reasonable to mention the interface or at least a relevant package and say that further details can be checked on the the Java documentation if you're pressed for more specificity, given that's what it's there for in the first place.

We can store the values in a map and search words in the map (but got stuck how to decide key-value pair in the map).

Given the wording, my interpretation of their question was not "which data structure would you use?", but rather, "which pre-existing search algorithm would you choose?". It seems to me like it was them who needed to answer the question regarding DS.

That said, if you had indeed been asked "which data structure would you use?", then a Map would've still worked against you, since you didn't really need to map a key to a value. You only needed to store a value (i.e. the words). Therefore, a Set, specifically a HashSet, would've been a better candidate, since it also avoids duplicates and should consume less memory in the process because it stores singular values, rather than key/value pairs.

Of course, that's still under the assumption(s) I made earlier. If memory constraints are said to be an issue, then scaling horizontally to multiple servers and so on would've likely been necessary.

How can I understand the exact answer to this question and what can be the optimal solution(s)?

It is probably the case that they wanted to see if you would follow up with questions, given the lack of information they gave you.

Answer 2

The hashmap solution is reasonable as stated by others but there are doubts with respect to scalability.

Here is a possible solution for the problem as discussed in the below post

1. Sub-string match If your entry blob is a single sting or word (without any white space) and you need to search arbitrary sub-string within it. In such cases you need to parse every entry to find best possible entries that matches. One uses algorithms like Boyer Moor algorithm. See this and this for details. This is also equivalent to grep - because grep uses similar stuff inside

2. Indexed search. Here you are assuming that entry contains set of words and search is limited to fixed word lengths. In this case, entries are indexed over all the possible occurrences of words. This is often called "Full Text search". There are number of algorithms to do this and number of open source projects that can be used directly. Many of them, also support wild card search, approximate search etc. as below : a. Apache Lucene : http://lucene.apache.org/java/docs/index.html b. OpenFTS : http://openfts.sourceforge.net/ c. Sphinx http://sphinxsearch.com/

Most likely if you need "fixed words" as queries, the approach two will be very fast and effective

Reference - https://softwareengineering.stackexchange.com/questions/118759/how-to-quickly-search-through-a-very-large-list-of-strings-records-on-a-databa

Answer 3

You did not mention whether the entries are words or documents (multiple words). In both cases a search index could be suitable.

Search indexes extract words from the billion document entries and manage a map of these words to the documents they are used in. Frameworks like Lucene (e.g. as part of SOLR or ElasticSearch) manage memory and persistence for you.

If it were only multiple of thousands of entries, a simple HashMap would be sufficient because there is no need for memory management then. If all of the billion entries are single words, a database could be a slightly better choice.

Answer 4

Multi-billion entries lie at the edge of what might conceivably be stored in main memory (for instance, storing 10 billion entries at 100 bytes per entry will take 1000 GB main memory).

While storing the data in main memory offers a very high throughput (thousands to millions of requests per second), you'd likely need special hardware (typical blade servers only offers 16 GB, but there are commodity servers that permit installation of up to 3000 GB of main memory). Also, keeping this much data in the Java Heap will likely cause garbage collector pauses of seconds or minutes unless special care is taken.

Therefore, unless the structure of your data admits a very compact representation in main memory (say, you only need membership checking among ints, which is possible with a 512 MB Bitset), you'll not want to store it in main memory, but on disk.

Therefore, you'll need persistence. Any relational or NoSQL database permits efficient searching by key and can handle such amounts of data with ease. To talk to a relational database, use JPA or JDBC. To talk to a non-relational database, you can use their proprietary Java API or an abstraction layer such as Spring Data.

You could also implement persistence from scratch if you wanted to (i.e. the interviewer asks for that). A data structure optimized for efficient lookup in external memory is the B-Tree, that's what many databases use internally :-)

Answer 5

There are a couple data structures that allow for efficient searching, assuming that memory requirements aren't an issue and the data structure is already populated.

Regarding time complexity, Set#contains and Map#containsKey are both O(1), assuming that the hash function isn't expensive and that there aren't many collisions.

Because the data structure stores words (assuming you're referring to Strings), then it could also be relatively efficient to use a trie (radix tree, prefix tree, etc.), which would allow you to search by character (which I believe would be O(log n)). If the hash function is expensive or there are many collisions, this could be a good alternative!

The answer that you gave to the interviewer should suffice since hashing is an effective searching method, even for billions of entries.