Prints a table as a linear histogram in ASCII. This is intended to visualize small integer ranges, eg, 0 to 100.
Arguments:
- val_type: optional, column header.
- section_header: if the histogram has a secondary key, multiple tables will print and section_header can be used as a header description for each.
- section_print_fn: if section_print_fn is not None, it will be passed the bucket value.
Example:
```Python
b = BPF(text="""
BPF_HISTOGRAM(dist);
int kprobe__blk_account_io_completion(struct pt_regs *ctx, struct request *req)
{
dist.increment(req->__data_len / 1024);
return 0;
}
""")
[...]
b["dist"].print_linear_hist("kbytes")
```
Output:
```
kbytes : count distribution
0 : 3 |****** |
1 : 0 | |
2 : 0 | |
3 : 0 | |
4 : 19 |****************************************|
5 : 0 | |
6 : 0 | |
7 : 0 | |
8 : 4 |******** |
9 : 0 | |
10 : 0 | |
11 : 0 | |
12 : 0 | |
13 : 0 | |
14 : 0 | |
15 : 0 | |
16 : 2 |**** |
[...]
```
This is an efficient way to summarize data, as the summarization is performed in-kernel, and only the values in the count column are passed to user space.
Some helper methods provided by bcc. Note that since we're in Python, we can import any Python library and their methods, including, for example, the libraries: argparse, collections, ctypes, datetime, re, socket, struct, subprocess, sys, and time.
