InfluxDB TSM file: Python parsing library

InfluxDB is a scalable database optimized for storage of time series, real-time application metrics, operations monitoring events, etc, written in Go.

Data is stored in .tsm files, which are kept pretty simple conceptually. Each .tsm file contains a header and footer, which stores offset to an index. Index is used to find a data block for a requested time boundary.

Application

InfluxDB

File extension

tsm

KS implementation details

License: MIT

References

This page hosts a formal specification of InfluxDB TSM file using Kaitai Struct. This specification can be automatically translated into a variety of programming languages to get a parsing library.

Usage

Runtime library

All parsing code for Python generated by Kaitai Struct depends on the Python runtime library. You have to install it before you can parse data.

The Python runtime library can be installed from PyPI:

python3 -m pip install kaitaistruct

Code

Parse a local file and get structure in memory:

data = Tsm.from_file("path/to/local/file.tsm")

Or parse structure from a bytes:

from kaitaistruct import KaitaiStream, BytesIO

raw = b"\x00\x01\x02..."
data = Tsm(KaitaiStream(BytesIO(raw)))

After that, one can get various attributes from the structure by invoking getter methods like:

data.header # => get header

Python source code to parse InfluxDB TSM file

tsm.py

# This is a generated file! Please edit source .ksy file and use kaitai-struct-compiler to rebuild

from pkg_resources import parse_version
import kaitaistruct
from kaitaistruct import KaitaiStruct, KaitaiStream, BytesIO


if parse_version(kaitaistruct.__version__) < parse_version('0.9'):
    raise Exception("Incompatible Kaitai Struct Python API: 0.9 or later is required, but you have %s" % (kaitaistruct.__version__))

class Tsm(KaitaiStruct):
    """InfluxDB is a scalable database optimized for storage of time
    series, real-time application metrics, operations monitoring events,
    etc, written in Go.
    
    Data is stored in .tsm files, which are kept pretty simple
    conceptually. Each .tsm file contains a header and footer, which
    stores offset to an index. Index is used to find a data block for a
    requested time boundary.
    """
    def __init__(self, _io, _parent=None, _root=None):
        self._io = _io
        self._parent = _parent
        self._root = _root if _root else self
        self._read()

    def _read(self):
        self.header = Tsm.Header(self._io, self, self._root)

    class Header(KaitaiStruct):
        def __init__(self, _io, _parent=None, _root=None):
            self._io = _io
            self._parent = _parent
            self._root = _root if _root else self
            self._read()

        def _read(self):
            self.magic = self._io.read_bytes(4)
            if not self.magic == b"\x16\xD1\x16\xD1":
                raise kaitaistruct.ValidationNotEqualError(b"\x16\xD1\x16\xD1", self.magic, self._io, u"/types/header/seq/0")
            self.version = self._io.read_u1()


    class Index(KaitaiStruct):
        def __init__(self, _io, _parent=None, _root=None):
            self._io = _io
            self._parent = _parent
            self._root = _root if _root else self
            self._read()

        def _read(self):
            self.offset = self._io.read_u8be()

        class IndexHeader(KaitaiStruct):
            def __init__(self, _io, _parent=None, _root=None):
                self._io = _io
                self._parent = _parent
                self._root = _root if _root else self
                self._read()

            def _read(self):
                self.key_len = self._io.read_u2be()
                self.key = (self._io.read_bytes(self.key_len)).decode(u"UTF-8")
                self.type = self._io.read_u1()
                self.entry_count = self._io.read_u2be()
                self.index_entries = [None] * (self.entry_count)
                for i in range(self.entry_count):
                    self.index_entries[i] = Tsm.Index.IndexHeader.IndexEntry(self._io, self, self._root)


            class IndexEntry(KaitaiStruct):
                def __init__(self, _io, _parent=None, _root=None):
                    self._io = _io
                    self._parent = _parent
                    self._root = _root if _root else self
                    self._read()

                def _read(self):
                    self.min_time = self._io.read_u8be()
                    self.max_time = self._io.read_u8be()
                    self.block_offset = self._io.read_u8be()
                    self.block_size = self._io.read_u4be()

                class BlockEntry(KaitaiStruct):
                    def __init__(self, _io, _parent=None, _root=None):
                        self._io = _io
                        self._parent = _parent
                        self._root = _root if _root else self
                        self._read()

                    def _read(self):
                        self.crc32 = self._io.read_u4be()
                        self.data = self._io.read_bytes((self._parent.block_size - 4))


                @property
                def block(self):
                    if hasattr(self, '_m_block'):
                        return self._m_block if hasattr(self, '_m_block') else None

                    io = self._root._io
                    _pos = io.pos()
                    io.seek(self.block_offset)
                    self._m_block = Tsm.Index.IndexHeader.IndexEntry.BlockEntry(io, self, self._root)
                    io.seek(_pos)
                    return self._m_block if hasattr(self, '_m_block') else None



        @property
        def entries(self):
            if hasattr(self, '_m_entries'):
                return self._m_entries if hasattr(self, '_m_entries') else None

            _pos = self._io.pos()
            self._io.seek(self.offset)
            self._m_entries = []
            i = 0
            while True:
                _ = Tsm.Index.IndexHeader(self._io, self, self._root)
                self._m_entries.append(_)
                if self._io.pos() == (self._io.size() - 8):
                    break
                i += 1
            self._io.seek(_pos)
            return self._m_entries if hasattr(self, '_m_entries') else None


    @property
    def index(self):
        if hasattr(self, '_m_index'):
            return self._m_index if hasattr(self, '_m_index') else None

        _pos = self._io.pos()
        self._io.seek((self._io.size() - 8))
        self._m_index = Tsm.Index(self._io, self, self._root)
        self._io.seek(_pos)
        return self._m_index if hasattr(self, '_m_index') else None