This page has been obsoleted and replaced: https://systemd.io/JOURNAL_FILE_FORMAT.

Journal File Format

Note that this document describes the binary on-disk format of journals only. For interfacing with web technologies there's the Journal JSON Format. For transfer of journal data across the network there's the Journal Export Format.

The systemd journal stores log data in a binary format with several features:

Fully indexed by all fields
Can store binary data, up to 2^64-1 in size
Seekable
Primarily append-based, hence robust to corruption
Support for in-line compression
Support for in-line Forward Secure Sealing

This document explains the basic structure of the file format on disk. We are making this available primarily to allow review and provide documentation. Note that the actual implementation in the systemd codebase is the only ultimately authoritative description of the format, so if this document and the code disagree, the code is right. That said we'll of course try hard to keep this document up-to-date and accurate.

Instead of implementing your own reader or writer for journal files we ask you to use the Journal's native C API to access these files. It provides you with full access to the files, and will not withhold any data. If you find a limitation, please ping us and we might add some additional interfaces for you.

If you need access to the raw journal data in serialized stream form without C API our recommendation is to make use of the Journal Export Format, which you can get via "journalctl -o export" or via systemd-journal-gatewayd. The export format is much simpler to parse, but complete and accurate. Due to its stream-based nature it is not indexed.

Or, to put this in other words: this low-level document is probably not what you want to use as base of your project. You want our C API instead! And if you really don't want the C API, then you want the Journal Export Format instead! This document is primarily for your entertainment and education. Thank you!

This document assumes you have a basic understanding of the journal concepts, the properties of a journal entry and so on. If not, please go and read up, then come back! This is a good opportunity to read about the basic properties of journal entries, in particular realize that they may include binary non-text data (though usually don't), and the same field might have multiple values assigned within the same entry.

This document describes the current format of systemd 195. The documented format is compatible with the format used in the first versions of the journal, but received various compatible additions since.

If you are wondering why the journal file format has been created in the first place instead of adopting an existing database implementation, please have a look at this thread.

Basics

All offsets, sizes, time values, hashes (and most other numeric values) are 64bit unsigned integers in LE format.
Offsets are always relative to the beginning of the file.
The 64bit hash function used is Jenkins lookup3, more specifically jenkins_hashlittle2() with the first 32bit integer it returns as higher 32bit part of the 64bit value, and the second one uses as lower 32bit part.
All structures are aligned to 64bit boundaries and padded to multiples of 64bit
The format is designed to be read and written via memory mapping using multiple mapped windows.
All time values are stored in usec since the respective epoch.
Wall clock time values are relative to the Unix time epoch, i.e. January 1st, 1970. (CLOCK_REALTIME)
Monotonic time values are always stored jointly with the kernel boot ID value (i.e. /proc/sys/kernel/random/boot_id) they belong to. They tend to be relative to the start of the boot, but aren't for containers. (CLOCK_MONOTONIC)
Randomized, unique 128bit IDs are used in various locations. These are generally UUID v4 compatible, but this is not a requirement.

General Rules

If any kind of corruption is noticed by a writer it should immediately rotate the file and start a new one. No further writes should be attempted to the original file, but it should be left around so that as little data as possible is lost.

If any kind of corruption is noticed by a reader it should try hard to handle this gracefully, such as skipping over the corrupted data, but allowing access to as much data around it as possible.

A reader should verify all offsets and other data as it reads it. This includes checking for alignment and range of offsets in the file, especially before trying to read it via a memory map.

A reader must interleave rotated and corrupted files as good as possible and present them as single stream to the user.

All fields marked as "reserved" must be initialized with 0 when writing and be ignored on reading. They are currently not used but might be used later on.

Structure

The file format's data structures are declared in journal-def.h.

The file format begins with a header structure. After the header structure object structures follow. Objects are appended to the end as time progresses. Most data stored in these objects is not altered anymore after having been written once, with the exception of records necessary for indexing. When new data is appended to a file the writer first writes all new objects to the end of the file, and then links them up at front after that's done. Currently, seven different object types are known:

enum {
        OBJECT_UNUSED,
        OBJECT_DATA,
        OBJECT_FIELD,
        OBJECT_ENTRY,
        OBJECT_DATA_HASH_TABLE,
        OBJECT_FIELD_HASH_TABLE,
        OBJECT_ENTRY_ARRAY,
        OBJECT_TAG,
        _OBJECT_TYPE_MAX
};

A DATA object, which encapsulates the contents of one field of an entry, i.e. a string such as _SYSTEMD_UNIT=avahi-daemon.service, or MESSAGE=Foobar made a booboo. but possibly including large or binary data, and always prefixed by the field name and "=".
A FIELD object, which encapsulates a field name, i.e. a string such as _SYSTEMD_UNIT or MESSAGE, without any = or even value.
An ENTRY object, which binds several DATA objects together into a log entry.
A DATA_HASH_TABLE object, which encapsulates a hash table for finding existing DATA objects.
A FIELD_HASH_TABLE object, which encapsulates a hash table for finding existing FIELD objects.
An ENTRY_ARRAY object, which encapsulates a sorted array of offsets to entries, used for seeking by binary search.
A TAG object, consisting of an FSS sealing tag for all data from the beginning of the file or the last tag written (whichever is later).

The Header struct defines, well, you guessed it, the file header:

_packed_ struct Header {
        uint8_t signature[8]; /* "LPKSHHRH" */
        le32_t compatible_flags;
        le32_t incompatible_flags;
        uint8_t state;
        uint8_t reserved[7];
        sd_id128_t file_id;
        sd_id128_t machine_id;
        sd_id128_t boot_id;    /* last writer */
        sd_id128_t seqnum_id;
        le64_t header_size;
        le64_t arena_size;
        le64_t data_hash_table_offset;
        le64_t data_hash_table_size;
        le64_t field_hash_table_offset;
        le64_t field_hash_table_size;
        le64_t tail_object_offset;
        le64_t n_objects;
        le64_t n_entries;
        le64_t tail_entry_seqnum;
        le64_t head_entry_seqnum;
        le64_t entry_array_offset;
        le64_t head_entry_realtime;
        le64_t tail_entry_realtime;
        le64_t tail_entry_monotonic;
        /* Added in 187 */
        le64_t n_data;
        le64_t n_fields;
        /* Added in 189 */
        le64_t n_tags;
        le64_t n_entry_arrays;
};

The first 8 bytes of Journal files must contain the ASCII characters LPKSHHRH.

If a writer finds that the machine_id of a file to write to does not match the machine it is running on it should immediately rotate the file and start a new one.

When journal file is first created the file_id is randomly and uniquely initialized.

When a writer opens a file it shall initialize the boot_id to the current boot id of the system.

The currently used part of the file is the header_size plus the arena_size field of the header. If a writer needs to write to a file where the actual file size on disk is smaller than the reported value it shall immediately rotate the file and start a new one. If a writer is asked to write to a file with a header that is shorter than his own definition of the struct Header, he shall immediately rotate the file and start a new one.

The n_objects field contains a counter for objects currently available in this file. As objects are appended to the end of the file this counter is increased.

The first object in the file starts immediately after the header. The last object in the file is at the offset tail_object_offset, which may be 0 if no object is in the file yet.

The n_entries, n_data, n_fields, n_tags, n_entry_arrays are counters of the objects of the specific types.

tail_entry_seqnum and head_entry_seqnum contain the sequential number (see below) of the last or first entry in the file, respectively, or 0 if no entry has been written yet.

tail_entry_realtime and head_entry_realtime contain the wallclock timestamp of the last or first entry in the file, respectively, or 0 if no entry has been written yet.

tail_entry_monotonic is the monotonic timestamp of the last entry in the file, referring to monotonic time of the boot identified by boot_id.

Extensibility

The format is supposed to be extensible in order to enable future additions of features. Readers should simply skip objects of unknown types as they read them. If a compatible feature extension is made a new bit is registered in the header's 'compatible_flags' field. If a feature extension is used that makes the format incompatible a new bit is registered in the header's 'incompatible_flags' field. Readers should check these two bit fields, if they find a flag they don't understand in compatible_flags they should continue to read the file, but if they find one in 'incompatible_flags' they should fail, asking for an update of the software. Writers should refuse writing if there's an unknown bit flag in either of these fields.

The file header may be extended as new features are added. The size of the file header is stored in the header. All header fields up to "n_data" are known to unconditionally exist in all revisions of the file format, all fields starting with "n_data" needs to be explicitly checked for via a size check, since they were additions after the initial release.

Currently only two extensions flagged in the flags fields are known:

enum {
        HEADER_INCOMPATIBLE_COMPRESSED = 1
};

enum {
        HEADER_COMPATIBLE_SEALED = 1
};

HEADER_INCOMPATIBLE_COMPRESSED indicates that the file includes DATA objects that are compressed using XZ.

HEADER_COMPATIBLE_SEALED indicates that the file includes TAG objects required for Forward Secure Sealing.

Dirty Detection

enum {
        STATE_OFFLINE = 0,
        STATE_ONLINE = 1,
        STATE_ARCHIVED = 2,
        _STATE_MAX
};

If a file is opened for writing the state field should be set to STATE_ONLINE. If a file is closed after writing the state field should be set to STATE_OFFLINE. After a file has been rotated it should be set to STATE_ARCHIVED. If a writer is asked to write to a file that is not in STATE_OFFLINE it should immediately rotate the file and start a new one, without changing the file.

After and before the state field is changed fdatasync() should be executed on the file to ensure the dirty state hits disk.

Sequence Numbers

All entries carry sequence numbers that are monotonically counted up for each entry (starting at 1) and are unique among all files which carry the same seqnum_id field. This field is randomly generated when the journal daemon creates its first file. All files generated by the same journal daemon instance should hence carry the same seqnum_id. This should guarantee a monotonic stream of sequential numbers for easy interleaving even if entries are distributed among several files, such as the system journal and many per-user journals.

Concurrency

The file format is designed to be usable in a simultaneous single-writer/multiple-reader scenario. The synchronization model is very weak in order to facilitate storage on the most basic of file systems (well, the most basic ones that provide us with mmap() that is), and allow good performance. No file locking is used. The only time where disk synchronization via fdatasync() should be enforced is after and before changing the state field in the file header (see below). It is recommended to execute a memory barrier after appending and initializing new objects at the end of the file, and before linking them up in the earlier objects.

This weak synchronization model means that it is crucial that readers verify the structural integrity of the file as they read it and handle invalid structure gracefully. (Checking what you read is a pretty good idea out of security considerations anyway.) This specifically includes checking offset values, and that they point to valid objects, with valid sizes and of the type and hash value expected. All code must be written with the fact in mind that a file with inconsistent structure file might just be inconsistent temporarily, and might become consistent later on. Payload OTOH requires less scrutiny, as it should only be linked up (and hence visible to readers) after it was successfully written to memory (though not necessarily to disk). On non-local file systems it is a good idea to verify the payload hashes when reading, in order to avoid annoyances with mmap() inconsistencies.

Clients intending to show a live view of the journal should use inotify() for this to watch for files changes. Since file writes done via mmap() do not result in inotify() writers shall truncate the file to its current size after writing one or more entries, which results in inotify events being generated. Note that this is not used as transaction scheme (it doesn't protect anything), but merely for triggering wakeups.

Note that inotify will not work on network file systems if reader and writer reside on different hosts. Readers which detect they are run on journal files on a non-local file system should hence not rely on inotify for live views but fall back to simple time based polling of the files (maybe recheck every 2s).

Objects

All objects carry a common header:

enum {
        OBJECT_COMPRESSED = 1
};

_packed_ struct ObjectHeader {
        uint8_t type;
        uint8_t flags;
        uint8_t reserved[6];
        le64_t size;
        uint8_t payload[];
};

The type field is one of the object types listed above. The flags field currently knows one flag: OBJECT_COMPRESSED. It is only valid for DATA objects and indicates that the data payload is compressed with XZ. If OBJECT_COMPRESSED is set for an object HEADER_INCOMPATIBLE_COMPRESSED must be set for the file as well. The size field encodes the size of the object including all its headers and payload.

Data Objects

_packed_ struct DataObject {
        ObjectHeader object;
        le64_t hash;
        le64_t next_hash_offset;
        le64_t next_field_offset;
        le64_t entry_offset; /* the first array entry we store inline */
        le64_t entry_array_offset;
        le64_t n_entries;
        uint8_t payload[];
};

Data objects carry actual field data in the payload[] array, including a field name, a '=' and the field data. Example: _SYSTEMD_UNIT=foobar.service. The hash field is a hash value of the payload.

next_hash_offset is used to link up DATA objects in the DATA_HASH_TABLE if a hash collision happens (in a singly linked list, with an offset of 0 indicating the end). next_field_offset is used to link up data objects with the same field name from the FIELD object of the field used.

entry_offset is an offset to the first ENTRY object referring to this DATA object. entry_array_offset is an offset to an ENTRY_ARRAY object with offsets to other entries referencing this DATA object. Storing the offset to the first ENTRY object in-line is an optimization given that many DATA objects will be referenced from a single entry only (for example, MESSAGE= frequently includes a practically unique string). n_entries is a counter of the total number of ENTRY objects that reference this object, i.e. the sum of all ENTRY_ARRAYS chained up from this object, plus 1.

The payload[] field contains the field name and date unencoded, unless OBJECT_COMPRESSED is set in the ?ObjectHeader, in which case the payload is LZMA compressed.

Field Objects

_packed_ struct FieldObject {
        ObjectHeader object;
        le64_t hash;
        le64_t next_hash_offset;
        le64_t head_data_offset;
        uint8_t payload[];
};

Field objects are used to enumerate all possible values a certain field name can take in the entire journal file.

The payload[] array contains the actual field name, without '=' or any field value. Example: _SYSTEMD_UNIT. The hash field is a hash value of the payload.

next_hash_offset is used to link up FIELD objects in the FIELD_HASH_TABLE if a hash collision happens (in singly linked list, offset 0 indicating the end). head_data_offset points to the first DATA object that shares this field name. It is the head of a singly linked list using DATA's next_field_offset offset.

Entry Objects

_packed_ struct EntryItem {
        le64_t object_offset;
        le64_t hash;
};

_packed_ struct EntryObject {
        ObjectHeader object;
        le64_t seqnum;
        le64_t realtime;
        le64_t monotonic;
        sd_id128_t boot_id;
        le64_t xor_hash;
        EntryItem items[];
};

An ENTRY object binds several DATA objects together into one log entry, and includes other metadata such as various timestamps.

The seqnum field contains the sequence number of the entry, realtime the realtime timestamp, and monotonic the monotonic timestamp for the boot identified by boot_id.

The xor_hash field contains a binary XOR of the hashes of the payload of all DATA objects referenced by this ENTRY. This value is usable to check the contents of the entry, being independent of the order of the DATA objects in the array.

The items[] array contains references to all DATA objects of this entry, plus their respective hashes.

In the file ENTRY objects are written ordered monotonically by sequence number. For continuous parts of the file written during the same boot (i.e. with the same boot_id) the monotonic timestamp is monotonic too. Modulo wallclock time jumps (due to incorrect clocks being corrected) the realtime timestamps are monotonic too.

Hash Table Objects

_packed_ struct HashItem {
        le64_t head_hash_offset;
        le64_t tail_hash_offset;
};

_packed_ struct HashTableObject {
        ObjectHeader object;
        HashItem items[];
};

The structure of both DATA_HASH_TABLE and FIELD_HASH_TABLE objects are identical. They implement a simple hash table, which each cell containing offsets to the head and tail of the singly linked list of the DATA and FIELD objects, respectively. DATA's and FIELD's next_hash_offset field are used to chain up the objects. Empty cells have both offsets set to 0.

Each file contains exactly one DATA_HASH_TABLE and one FIELD_HASH_TABLE objects. Their payload is directly referred to by the file header in the data_hash_table_offset, data_hash_table_size, field_hash_table_offset, field_hash_table_size fields. These offsets do not point to the object headers but directly to the payloads. When a new journal file is created the two hash table objects need to be created right away as first two objects in the stream.

If the hash table fill level is increasing over a certain fill level (Learning from Java's Hashtable for example: > 75%), the writer should rotate the file and create a new one.

The DATA_HASH_TABLE should be sized taking into account to the maximum size the file is expected to grow, as configured by the administrator or disk space considerations. The FIELD_HASH_TABLE should be sized to a fixed size, as the number of fields should be pretty static it depends only on developers' creativity rather than runtime parameters.

Entry Array Objects

_packed_ struct EntryArrayObject {
        ObjectHeader object;
        le64_t next_entry_array_offset;
        le64_t items[];
};

Entry Arrays are used to store a sorted array of offsets to entries. Entry arrays are strictly sorted by offsets on disk, and hence by their timestamps and sequence numbers (with some restrictions, see above).

Entry Arrays are chained up. If one entry array is full another one is allocated and the next_entry_array_offset field of the old one pointed to it. An Entry Array with next_entry_array_offset set to 0 is the last in the list. To optimize allocation and seeking, as entry arrays are appended to a chain of entry arrays they should increase in size (double).

Due to being monotonically ordered entry arrays may be searched with a binary search (bisection).

One chain of entry arrays links up all entries written to the journal. The first entry array is referenced in the entry_array_offset field of the header.

Each DATA object also references an entry array chain listing all entries referencing a specific DATA object. Since many DATA objects are only referenced by a single ENTRY the first offset of the list is stored inside the DATA object itself, an ENTRY_ARRAY object is only needed if it is referenced by more than one ENTRY.

Tag Object

#define TAG_LENGTH (256/8)

_packed_ struct TagObject {
        ObjectHeader object;
        le64_t seqnum;
        le64_t epoch;
        uint8_t tag[TAG_LENGTH]; /* SHA-256 HMAC */
};

Tag objects are used to seal off the journal for alteration. In regular intervals a tag object is appended to the file. The tag object consists of a SHA-256 HMAC tag that is calculated from the objects stored in the file since the last tag was written, or from the beginning if no tag was written yet. The key for the HMAC is calculated via the externally maintained FSPRG logic for the epoch that is written into epoch. The sequence number seqnum is increased with each tag. When calculating the HMAC of objects header fields that are volatile are excluded (skipped). More specifically all fields that might validly be altered to maintain a consistent file structure (such as offsets to objects added later for the purpose of linked lists and suchlike) after an object has been written are not protected by the tag. This means a verifier has to independently check these fields for consistency of structure. For the fields excluded from the HMAC please consult the source code directly. A verifier should read the file from the beginning to the end, always calculating the HMAC for the objects it reads. Each time a tag object is encountered the HMAC should be verified and restarted. The tag object sequence numbers need to increase strictly monotonically. Tag objects themselves are partially protected by the HMAC (i.e. seqnum and epoch is included, the tag itself not).

Algorithms

Reading:

Given an offset to an entry all data fields are easily found by following the offsets in the data item array of the entry.

Listing entries without filter is done by traversing the list of entry arrays starting with the headers' entry_array_offset field.

Seeking to an entry by timestamp or sequence number (without any matches) is done via binary search in the entry arrays starting with the header's entry_array_offset field. Since these arrays double in size as more are added the time cost of seeking is O(log(n)*log(n)) if n is the number of entries in the file.

When seeking or listing with one field match applied the DATA object of the match is first identified, and then its data entry array chain traversed. The time cost is the same as for seeks/listings with no match.

If multiple matches are applied, multiple chains of entry arrays should be traversed in parallel. Since they all are strictly monotonically ordered by offset of the entries, advancing in one can be directly applied to the others, until an entry matching all matches is found. In the worst case seeking like this is O(n) where n is the number of matching entries of the "loosest" match, but in the common case should be much more efficient at least for the well-known fields, where the set of possible field values tend to be closely related. Checking whether an entry matches a number of matches is efficient since the item array of the entry contains hashes of all data fields referenced, and the number of data fields of an entry is generally small (< 30).

When interleaving multiple journal files seeking tends to be a frequently used operation, but in this case can be effectively suppressed by caching results from previous entries.

When listing all possible values a certain field can take it is sufficient to look up the FIELD object and follow the chain of links to all DATA it includes.

Writing:

When an entry is appended to the journal for each of its data fields the data hash table should be checked. If the data field does not yet exist in the file it should be appended and added to the data hash table. When a field data object is added the field hash table should be checked for the field name of the data field, and a field object be added if necessary. After all data fields (and recursively all field names) of the new entry are appended and linked up in the hashtables the entry object should be appended and linked up too.

In regular intervals a tag object should be written if sealing is enabled (see above). Before the file is closed a tag should be written too, to seal it off.

Before writing an object, time and disk space limits should be checked and rotation triggered if necessary.

Optimizing Disk IO

A few general ideas to keep in mind:

The hash tables for looking up fields and data should be quickly in the memory cache and not hurt performance. All entries and entry arrays are ordered strictly by time on disk, and hence should expose an OK access pattern on rotating media, when read sequentially (which should be the most common case, given the nature of log data).

The disk access patterns of the binary search for entries needed for seeking are problematic on rotating disks. This should not be a major issue though, since seeking should not be a frequent operation.

When reading, collecting data fields for presenting entries to the user is problematic on rotating disks. In order to optimize these patterns the item array of entry objects should be sorted by disk offset before writing. Effectively, frequently used data objects should be in the memory cache quickly. Non-frequently used data objects are likely to be located between the previous and current entry when reading and hence should expose an OK access pattern. Problematic are data objects that are neither frequently nor infrequently referenced, which will cost seek time.

And that's all there is to it.

Thanks for your interest!