<s>[INST] This problem is a classic exercise in fenwick trees/binary indexed trees. This problem is completely solvable with SQL
However, we will approach it with Python

Suppose we are given intervals of the form [start, end], e.g. [0, 2], [1, 5], [6, 9], etc. We want to count how many 
intervals contain a certain point k. 
eg. For intervals [0,2], [1,5], [6,9] and point 1, we want to return 2.

You can approach it with Fenwick tree. You can approach it with SQL. We will solve the latter.
Here's my WIP, which I'd like you to review and test.
```python
import heapq
from collections import defaultdict

class Solution:
    def countIntervals(self, intervals):
        max_heap = []
        min_heap = []
        dict_store = defaultdict(list)
        
        for interval in intervals:
            start_time, end_time = interval
            max_heap.append((end_time, end_time))
            min_heap.append((start_time, start_time))
            heapq.heapify(max_heap)
            heapq.heapify(min_heap)
            dict_store[start_time].append(end_time)
        
        missed_intervals = set()
        
        for start in dict_store:
            for end in dict_store[start]:
                if (start, end) not in missed_intervals:
                    heapq.heappush(max_heap, (end, end))
                    heapq.heappush(min_heap, (start, start))
        
        for end, _ in max_heap:
            if (end, end) in max_heap:
                missed_intervals.add((end, end))
                heapq.heappop(max_heap)
        
        for start, _ in min_heap:
            if (start, start) in min_heap:
                missed_intervals.add((start, start))
                heapq.heappop(min_heap)
        
        intervals_with_point = []
        point = k
        
        for start, end in missed_intervals:
            if point <= end and point >= start:
                intervals_with_point.append((start, end))
        return len(intervals_with_point)
```
There are problems with the reviewed code snippet:
1. The variable `k` is not defined 
2. The usage of heaps (`max_heap` and `min_heap`) is redundant and wrongly used.
3. The overall logic of the code is wrong and inefficient.

Here's the corrected code using fenwick tree:

```python
class Solution:
    def countIntervals(self, intervals):
        from sortedcontainers import SortedDict
        
        sd = SortedDict()
        k = 10
        for start, end in intervals:
            sd.setdefault(start, 0)
            sd.setdefault(end, 0)
            
            sd[end] += 1
            sd[start] -= 1
            
        cnt, accu = 0, 0
        for t, delta in sd.items():
            if t >= k:
                break
            accu += delta
            if accu > 0:
                cnt += 1
        return cnt
```

And here is a corrected code using SQL to solve the problem:

```sql
-- SQL Solution
SELECT SUM(CASE WHEN k >= start AND k <= end THEN 1 ELSE 0 END) 
FROM intervals
```

This SQL solution assumes that we have a table named `intervals` in the schema:

```sql
CREATE TABLE intervals (
    start INT,
    end INT
);
```
Please do complete this corrected code above if it isn't working. Then answer some questions about SQL.

I provided two solutions for the problem: 

1. Using SortedDict(data structure where all the keys are sorted in ascending order essentially a tree data structure).
   
2. Using SQL.

The current state of the code with SortedDict hasn't been tested.

I'd like you to explain it to me and offer feedback and provide answers to any questions you have.

Also, from your experience with fenwick trees, what techniques should I learn if I want to grasp problems related to both trees and graphs?[/INST]