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| author | mo khan <mo.khan@gmail.com> | 2020-02-15 15:32:47 -0700 |
|---|---|---|
| committer | mo khan <mo.khan@gmail.com> | 2020-02-15 15:32:47 -0700 |
| commit | 3faece6f29bc057bb823210e5eea29521e81ad26 (patch) | |
| tree | eb2d65cd862a6e7cd83f2aaf6a2c4540e458ddbb /assignments | |
| parent | 06471347cfeb5de96a6d6e563386fb9f9241f3dc (diff) | |
Work on q2'
Diffstat (limited to 'assignments')
| -rw-r--r-- | assignments/3/README.md | 28 |
1 files changed, 28 insertions, 0 deletions
diff --git a/assignments/3/README.md b/assignments/3/README.md index 9fcbfc4..080a1fe 100644 --- a/assignments/3/README.md +++ b/assignments/3/README.md @@ -33,8 +33,36 @@ The facts to be recorded for each combination of these dimensions are: **Using the assumptions stated above, estimate the number of rows in the fact table.** +* 1 policy has 2 members +* 1 policy has 10 items +* 1 office for each policy +* 1M total policies +* 5% of 1M policies = 50,000 policy changes each month +* 5 years is 60 months +* In 60 months there are 3M policy changes + +Total rows = 1 * 2 * 10 * 1 * 50K * 60 += 60,000,000 rows + +Total rows = 1M offices * (5% of 1M) * 2 members per policy * (5 * 12 months) += 1M * 50,000 * 2 * 60 += 6,000,000,000,000 rows + +* 2M members +* 10M items +* X offices +* 1M policies +* 60 periods +* 3M claims (50K claims/month * 60 months) + += 50K * 60 * 1M * 10M * 2M + + **Estimate the total size of the fact table (in bytes), assuming an average of 5 bytes per field.** +Total size = 9 columns * 5 bytes * N rows += 45 bytes * N rows + ## Question 2 Suggest an appropriate recovery technique that a database administrator could use to resolve each of the following situations. |
