Revert the unintended change that DestroyDB() doesn't clean up info logs.

Summary: A previous change triggered a change by mistake: DestroyDB() will keep info logs under DB directory. Revert the unintended change.

Test Plan: Add a unit test case to verify it.

Reviewers: ljin, yhchiang, igor

Reviewed By: igor

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22209
Eliminate VersionSet memory leak

Summary:
ManifestDumpCommand::DoCommand was allocating a VersionSet and never
freeing it.

Test Plan: make

Reviewers: igor

Reviewed By: igor

Differential Revision: https://reviews.facebook.net/D22221
Improve Options sanitization and add MmapReadRequired() to TableFactory

Summary:
Currently, PlainTable must use mmap_reads.  When PlainTable is used but
allow_mmap_reads is not set, rocksdb will fail in flush.

This diff improve Options sanitization and add MmapReadRequired() to
TableFactory.

Test Plan:
export ROCKSDB_TESTS=PlainTableOptionsSanitizeTest
make db_test -j32
./db_test

Reviewers: sdong, ljin

Reviewed By: ljin

Subscribers: you, leveldb

Differential Revision: https://reviews.facebook.net/D21939
Add missing implementaiton of SanitizeDBOptions in simple_table_db_test.cc

Summary:
Add missing implementaiton of SanitizeDBOptions in simple_table_db_test.cc

Test Plan:
make simple_table_db_test.cc
Fix the error of c_test.c

Summary:
Fix the error of c_test.c

Test Plan:
make c_test
./c_test
Implement Prepare method in CuckooTableReader

Summary:
- Implement Prepare method
- Rewrite performance tests in cuckoo_table_reader_test to write new file only if one doesn't already exist.
- Add performance tests for batch lookup along with prefetching.

Test Plan:
./cuckoo_table_reader_test --enable_perf
Results (We get better results if we used int64 comparator instead of string comparator (TBD in future diffs)):
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.208us (4.8 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.182us (5.5 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.161us (6.2 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.161us (6.2 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.500000, number of hash functions used: 2.
Time taken per op is 0.163us (6.1 Mqps) with batch size of 100

With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.252us (4.0 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.192us (5.2 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.195us (5.1 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.191us (5.2 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.600000, number of hash functions used: 3.
Time taken per op is 0.194us (5.1 Mqps) with batch size of 100

With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.228us (4.4 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.185us (5.4 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.186us (5.4 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.189us (5.3 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.750000, number of hash functions used: 3.
Time taken per op is 0.188us (5.3 Mqps) with batch size of 100

With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.325us (3.1 Mqps) with batch size of 0
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.196us (5.1 Mqps) with batch size of 10
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.199us (5.0 Mqps) with batch size of 25
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.196us (5.1 Mqps) with batch size of 50
With 100000000 items and hash table ratio 0.900000, number of hash functions used: 3.
Time taken per op is 0.209us (4.8 Mqps) with batch size of 100

Reviewers: sdong, yhchiang, igor, ljin

Reviewed By: ljin

Subscribers: leveldb

Differential Revision: https://reviews.facebook.net/D22167
Replace naked calls to operator new and delete (Fixes #222)

This replaces a mishmash of pointers in the Block and BlockContents classes with
std::unique_ptr. It also changes the semantics of BlockContents to be limited to
use as a constructor parameter for Block objects, as it owns any block buffers
handed to it.