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System Tables

Table of contents

Database Metadata System Tables

dolt_branches

dolt_branches contains information about branches known to the database.

Because the branch information is global to all clients, not just your session, dolt_branches system table is read-only. Branches can be created or deleted with the DOLT_BRANCH() stored procedure.

Schema

+------------------------+----------+
| Field                  | Type     |
+------------------------+----------+
| name                   | TEXT     |
| hash                   | TEXT     |
| latest_committer       | TEXT     |
| latest_committer_email | TEXT     |
| latest_commit_date     | DATETIME |
| latest_commit_message  | TEXT     |
| remote                 | TEXT     |
| branch                 | TEXT     |
| dirty                  | BOOLEAN  |
+------------------------+----------+

Example Queries

Get all the branches.

remote and branch show the remote host and branch that each branch is tracking.

dirty is TRUE when there are uncommitted changed on the branch.

To find the current active branch use select active_branch().

dolt_branches only contains information about local branches. For branches on a remote you have fetched, see dolt_remote_branches.

dolt_remote_branches

dolt_remote_branches contains information about branches on remotes you have fetched. It has a similar schema as dolt_branches, but the remote, branch, and dirty columns don't make sense in this context and are not included. Only remote branches are included in this table.

Schema

+------------------------+----------+
| Field                  | Type     |
+------------------------+----------+
| name                   | TEXT     |
| hash                   | TEXT     |
| latest_committer       | TEXT     |
| latest_committer_email | TEXT     |
| latest_commit_date     | DATETIME |
| latest_commit_message  | TEXT     |
+------------------------+----------+

Example Queries

Get all local and remote branches in a single query. Remote branches will have the prefix remotes/<remoteName> in their names.

SELECT *
FROM dolt_branches
UNION
SELECT * FROM dolt_remote_branches;
+-----------------+----------------------------------+------------------+------------------------+-------------------------+----------------------------+
| name            | hash                             | latest_committer | latest_committer_email | latest_commit_date      | latest_commit_message      |
+-----------------+----------------------------------+------------------+------------------------+-------------------------+----------------------------+
| main            | r3flrdqk73lkcrugtbohcdbb3hmr2bev | Zach Musgrave    | [email protected]       | 2023-02-01 18:59:55.156 | Initialize data repository |
| remotes/rem1/b1 | r3flrdqk73lkcrugtbohcdbb3hmr2bev | Zach Musgrave    | [email protected]       | 2023-02-01 18:59:55.156 | Initialize data repository |
+-----------------+----------------------------------+------------------+------------------------+-------------------------+----------------------------+

dolt_docs

dolt_docs stores the contents of Dolt docs (LICENSE.md, README.md).

You can modify the contents of these files via SQL, but you are not guaranteed to see these changes reflected in the files on disk.

Schema

+----------+------+
| field    | type |
+----------+------+
| doc_name | text |
| doc_text | text |
+----------+------+

Example

Gets all docs.

dolt_procedures

dolt_procedures stores each stored procedure that has been created on the database.

The values in this table are implementation details associated with the storage of stored procedures. It is recommended to use built-in SQL statements for examining and modifying stored procedures rather than using this table directly.

Schema

+-------------+----------+
| field       | type     |
+-------------+----------+
| name        | longtext |
| create_stmt | longtext |
| created_at  | datetime |
| modified_at | datetime |
| sql_mode    | longtext |
+-------------+----------+

When using the standard CREATE PROCEDURE workflow, the name column will always be lowercase. Dolt assumes that name is always lowercase as a result, and manually inserting a stored procedure must also have a lowercase name. Otherwise, it will be invisible to some operations, such as DROP PROCEDURE.

Example Query

CREATE PROCEDURE simple_proc1(x DOUBLE, y DOUBLE) SELECT x*y;
CREATE PROCEDURE simple_proc2() SELECT name FROM category;

dolt_query_catalog

The dolt_query_catalog system table stores named queries for your database. Like all data stored in Dolt, these named queries are versioned alongside your data, so after you create, modify, or remove a named query, you'll need to commit that change to save it. You can use the Dolt CLI to save and execute named queries or you can use the dolt_query_catalog system table directly to add, modify, or delete named queries. All named queries are displayed in the Queries tab of your database on DoltHub.

Schema

+---------------+-----------------+------+-----+---------+-------+
| Field         | Type            | Null | Key | Default | Extra |
+---------------+-----------------+------+-----+---------+-------+
| id            | varchar(16383)  | NO   | PRI |         |       |
| display_order | bigint unsigned | NO   |     |         |       |
| name          | varchar(16383)  | YES  |     |         |       |
| query         | varchar(16383)  | YES  |     |         |       |
| description   | varchar(16383)  | YES  |     |         |       |
+---------------+-----------------+------+-----+---------+-------+

Example Query

Using the dolthub/docs_examples from DoltHub as an example, you can create a named query using the CLI, or by directly inserting into the dolt_query_catalog table.

> dolt sql -q "select * from tablename" -s "select all" -m "Query to select all records from tablename"

After creating a named query, you can view it in the dolt_query_catalog table:

Then you can use the dolt CLI to execute it:

> dolt sql -x "Large Irises"
Executing saved query 'Large Irises':
select distinct(class) from classified_measurements where petal_length_cm > 5
+------------+
| class)     |
+------------+
| versicolor |
| virginica  |
+------------+

Last, but not least, if you want to persist that named query, be sure to commit your change to the dolt_query_catalog table.

dolt add dolt_query_catalog
dolt commit -m "Adding new named query"

dolt_remotes

dolt_remotes returns the remote subcontents of the repo_state.json, similar to running dolt remote -v from the command line.

The dolt_remotes table is currently read only. Use the CLI dolt remote functions or dolt_remote() procedure to add, update or delete remotes.

Schema

+-------------+------+------+-----+---------+-------+
| Field       | Type | Null | Key | Default | Extra |
+-------------+------+------+-----+---------+-------+
| name        | text | NO   | PRI |         |       |
| url         | text | NO   |     |         |       |
| fetch_specs | json | YES  |     |         |       |
| params      | json | YES  |     |         |       |
+-------------+------+------+-----+---------+-------+

Example Query

SELECT *
FROM dolt_remotes
WHERE name = 'origin';
+--------+-----------------------------------------+--------------------------------------+--------+
| name   | url                                     | fetch_specs                          | params |
+--------+-----------------------------------------+--------------------------------------+--------+
| origin | file:///go/github.com/dolthub/dolt/rem1 | [refs/heads/*:refs/remotes/origin/*] | map[]  |
+--------+-----------------------------------------+--------------------------------------+--------+

dolt_backups

dolt_backups returns the backup contents of the repo_state.json, similar to running dolt backup -v from the command line.

The dolt_backups table is currently read-only. Use the dolt_backup() procedure to add, update, or delete backups.

Schema

+-------------+------+------+-----+---------+-------+
| Field       | Type | Null | Key | Default | Extra |
+-------------+------+------+-----+---------+-------+
| name        | text | NO   | PRI |         |       |
| url         | text | NO   |     |         |       |
+-------------+------+------+-----+---------+-------+

Example Query

sql SELECT * FROM dolt_backups;

+-------------+----------------------------------------+
| name        | url                                    |
+-------------+----------------------------------------+
| backup-west | aws://[ddb-westtable:s3bucket-west]/db |
| backup-east | aws://[ddb-easttable:s3bucket-east]/db |
| backup-local| file:///path/to/local/backup           |
+-------------+----------------------------------------+

dolt_schemas

dolt_schemas stores SQL schema fragments for a dolt database that are versioned alongside the database itself. Certain DDL statements will modify this table and the value of this table in a SQL session will affect what database entities exist in the session.

The values in this table are implementation details associated with the storage of certain schema elements. It is recommended to use built-in SQL statements for examining and modifying schemas, rather than using this table directly.

Schema

+----------+----------------------------------------+------+-----+---------+-------+
| Field    | Type                                   | Null | Key | Default | Extra |
+----------+----------------------------------------+------+-----+---------+-------+
| type     | varchar(64) COLLATE utf8mb4_0900_ai_ci | NO   | PRI | NULL    |       |
| name     | varchar(64) COLLATE utf8mb4_0900_ai_ci | NO   | PRI | NULL    |       |
| fragment | longtext                               | YES  |     | NULL    |       |
| extra    | json                                   | YES  |     | NULL    |       |
+----------+----------------------------------------+------+-----+---------+-------+

Currently, all VIEW, TRIGGER and EVENT definitions are stored in the dolt_schemas table. The column type defines whether the fragment is view, trigger or event. The column name is the fragment name as supplied in the CREATE statement. The column fragment stores the CREATE statement of the fragment. The column json is any additional important information such as CreateAt field for the fragment.

The values in this table are partly implementation details associated with the implementation of the underlying database objects.

Example Query

CREATE VIEW four AS SELECT 2+2 FROM dual;
CREATE TABLE mytable (x INT PRIMARY KEY);
CREATE TRIGGER inc_insert BEFORE INSERT ON mytable FOR EACH ROW SET NEW.x = NEW.x + 1;
CREATE EVENT monthly_gc ON SCHEDULE EVERY 1 MONTH DO CALL DOLT_GC();

Then you can view them in dolt_schemas:

dolt_tags

dolt_tags shows information for all active tags in the current database.

DOLT_TAG() procedure can be used to INSERT and DELETE tags on the dolt_tags table.

Schema

+----------+----------+------+-----+---------+-------+
| Field    | Type     | Null | Key | Default | Extra |
+----------+----------+------+-----+---------+-------+
| tag_name | text     | NO   | PRI | NULL    |       |
| tag_hash | text     | NO   | PRI | NULL    |       |
| tagger   | text     | NO   |     | NULL    |       |
| email    | text     | NO   |     | NULL    |       |
| date     | datetime | NO   |     | NULL    |       |
| message  | text     | NO   |     | NULL    |       |
+----------+----------+------+-----+---------+-------+

Example Query

Create a tag using dolt_tag() stored procedure.

CALL DOLT_TAG('_migrationtest','head','-m','savepoint for migration testing');
+--------+
| status |
+--------+
| 0      |
+--------+

Get all the tags.

dolt_branch_activity

dolt_branch_activity provides insights into branch usage within the lifetime of a running dolt sql-server. This table helps administrators identify stale or unused branches. The data is global to the server, and it not related to the persisted data in the database. For the reason, the system_start_time column will always be the start time of your server, and the last_read and last_write columns should be considered in relation to that time. Activity for branches which have been deleted will not be included in this table.

Schema

+-------------------+----------+------+-----+---------+-------+
| Field             | Type     | Null | Key | Default | Extra |
+-------------------+----------+------+-----+---------+-------+
| branch            | text     | NO   | PRI | NULL    |       |
| last_read         | datetime | YES  |     | NULL    |       |
| last_write        | datetime | YES  |     | NULL    |       |
| active_sessions   | int      | NO   |     | NULL    |       |
| system_start_time | datetime | NO   |     | NULL    |       |
+-------------------+----------+------+-----+---------+-------+

Column Descriptions

  • branch: The name of the branch. All current branches are listed, even if unused.

  • last_read: The last time the branch was accessed in a query or checked out. NULL indicates no reads during the server's lifetime.

  • last_write: The last time the branch was updated or committed to. NULL indicates no writes during the server's lifetime.

  • active_sessions: The number of active server connections to the branch.

  • system_start_time: The server's start time. All last_read and last_write timestamps occur after this time.

Example Queries

Find branches with no active sessions and no activity in the last 7 days:

SELECT *
FROM dolt_branch_activity
WHERE active_sessions = 0
  AND system_start_time < NOW() - INTERVAL 7 DAY
  AND (last_read  IS NULL OR last_read  < NOW() - INTERVAL 7 DAY)
  AND (last_write IS NULL OR last_write < NOW() - INTERVAL 7 DAY);

dolt_statistics

dolt_statistics includes currently collected database statistics. This information is stored outside of the commit graph and is not subject to versioning semantics.

Schema

+-----------------+----------+------+-----+---------+-------+
| Field           | Type     | Null | Key | Default | Extra |
+-----------------+----------+------+-----+---------+-------+
| database_name   | text     | NO   | PRI | NULL    |       |
| table_name      | text     | NO   | PRI | NULL    |       |
| index_name      | text     | NO   | PRI | NULL    |       |
| row_count       | bigint   | NO   |     | NULL    |       |
| distinct_count  | bigint   | NO   |     | NULL    |       |
| null_count      | bigint   | NO   |     | NULL    |       |
| columns         | text     | NO   |     | NULL    |       |
| types           | text     | NO   |     | NULL    |       |
| upper_bound     | text     | NO   |     | NULL    |       |
| upper_bound_cnt | bigint   | NO   |     | NULL    |       |
| created_at      | datetime | NO   |     | NULL    |       |
| mcv1            | text     | NO   |     | NULL    |       |
| mcv2            | text     | NO   |     | NULL    |       |
| mcv3            | text     | NO   |     | NULL    |       |
| mcv4            | text     | NO   |     | NULL    |       |
| mcvCounts       | text     | NO   |     | NULL    |       |
+-----------------+----------+------+-----+---------+-------+

Database History System Tables

dolt_blame_$tablename

For every user table that has a primary key, there is a queryable system view named dolt_blame_$tablename which can be queried to see the user and commit responsible for the current value of each row. This is equivalent to the dolt blame CLI command. Tables without primary keys will not have an associated dolt_blame_$tablename.

Schema

The dolt_blame_$tablename system view has the following columns:

+-------------------+----------+
| field             | type     |
+-------------------+----------+
| commit            | text     |
| commit_date       | datetime |
| committer         | text     |
| email             | text     |
| message           | text     |
| primary key cols  |          |
+-------------------+----------+

The remaining columns are dependent on the schema of the user table. Every column from the primary key of your table will be included in the dolt_blame_$tablename system table.

Query Details

Executing a SELECT * query for a dolt_blame_$tablename system view will show you the primary key columns for every row in the underlying user table and the commit metadata for the last commit that modified that row. Note that if a table has any uncommitted changes in the working set, those will not be displayed in the dolt_blame_$tablename system view.

dolt_blame_$tablename is only available for tables with a primary key. Attempting to query dolt_blame_$tablename for a table without a primary key will return an error message.

Example Query

Consider the following example table city:

To find who set the current values, we can query the dolt_blame_city table:

dolt_commit_ancestors

The dolt_commit_ancestors table records the ancestors for every commit in the database. Each commit has one or two ancestors, two in the case of a merge commit.

Schema

Each commit hash has one or two entries in the table, depending on whether it has one or two parent commits. The root commit of the database has a NULL parent. For merge commits, the merge base will have parent_index 0, and the commit merged will have parent_index 1.

+--------------+------+------+-----+---------+-------+
| Field        | Type | Null | Key | Default | Extra |
+--------------+------+------+-----+---------+-------+
| commit_hash  | text | NO   | PRI |         |       |
| parent_hash  | text | NO   | PRI |         |       |
| parent_index | int  | NO   | PRI |         |       |
+--------------+------+------+-----+---------+-------+

dolt_commits

The dolt_commits system table shows ALL commits in a Dolt database.

This is similar, but different from the dolt_log system table and the dolt log CLI command. dolt log shows you commit history for all commit ancestors reachable from the current HEAD of the checked out branch, whereas dolt_commits shows all commits from the entire database, no matter which branch is checked out.

Schema

> describe dolt_commits;
+-------------+----------+------+-----+---------+-------+
| Field       | Type     | Null | Key | Default | Extra |
+-------------+----------+------+-----+---------+-------+
| commit_hash | text     | NO   | PRI |         |       |
| committer   | text     | NO   |     |         |       |
| email       | text     | NO   |     |         |       |
| date        | datetime | NO   |     |         |       |
| message     | text     | NO   |     |         |       |
+-------------+----------+------+-----+---------+-------+

Example Query

Using the dolthub/first-hour-db database from DoltHub, we can query for the five commits before April 20th, 2022, across all commits in the database (regardless of what is checked out to HEAD) with this query:

dolt_history_$TABLENAME

For every user table named $TABLENAME, there is a read-only system table named dolt_history_$TABLENAME that can be queried to find a row's value at every commit in the current branch's history.

Schema

Every Dolt history table contains columns for commit_hash, committer, and commit_date, plus every column from the user table's schema at the current checked out branch.

+-------------+----------+
| field       | type     |
+-------------+----------+
| commit_hash | TEXT     |
| committer   | TEXT     |
| commit_date | DATETIME |
| other cols  |          |
+-------------+----------+

Example Schema

Consider a table named mytable with the following schema:

+------------+--------+
| field      | type   |
+------------+--------+
| x          | INT    |
+------------+--------+

The schema for dolt_history_mytable would be:

+-------------+----------+
| field       | type     |
+-------------+----------+
| x           | INT      |
| commit_hash | TEXT     |
| committer   | TEXT     |
| commit_date | DATETIME |
+-------------+----------+

Example Query

Assume a database with the mytable table above and the following commit graph:

   B---E  feature
  /
 A---C---D  main

When the feature branch is checked out, the following query returns the results below, showing the row at every ancestor commit reachable from our current branch.

dolt_log

The dolt_log system table contains the commit log for all commits reachable from the current HEAD. This is the same data returned by the dolt log CLI command.

Schema

+--------------+----------+
| field        | type     |
+--------------+--------- +
| commit_hash  | text     |
| committer    | text     |
| email        | text     |
| date         | datetime |
| message      | text     |
| commit_order | int      |
+--------------+--------- +

The commit_order field is an integer value that indicates the order of commits in descending order from HEAD. Note that commit_order values can be repeated for different levels of the topological sort of the commit graph.

Example Query

The following query shows the commits reachable from the current checked out head and created by user jennifersp since April, 2022:

Database Diffs

dolt_commit_diff_$TABLENAME

For every user table named $TABLENAME, there is a read-only system table named dolt_commit_diff_$TABLENAME that can be queried to see a diff of the data in the specified table between any two commits in the database. For example, you can use this system table to view the diff between two commits on different branches. The schema of the returned data from this system table is based on the schema of the underlying user table at the currently checked out branch.

You must provide from_commit and to_commit in all queries to this system table in order to specify the to and from points for the diff of your table data. Each returned row describes how a row in the underlying user table has changed from the from_commit ref to the to_commit ref by showing the old and new values.

dolt_commit_diff_$TABLENAME is the analogue of the dolt diff CLI command. It represents the two-dot diff between the two commits provided. The dolt_diff_$TABLENAME system table also exposes diff information, but instead of a two-way diff, it returns a log of individual diffs between all adjacent commits in the history of the current branch. In other words, if a row was changed in 10 separate commits, dolt_diff_$TABLENAME will show 10 separate rows – one for each individual delta. In contrast, dolt_commit_diff_$TABLENAME would show a single row that combines all the individual commit deltas into one diff.

The DOLT_DIFF() table function is an alternative to the dolt_commit_diff_$tablename system table for cases where a table's schema has changed between the to and from commits. Consider the DOLT_DIFF() table function if you need to see the schema from each of those commits, instead of using the schema from the currently checked out branch.

Schema

+------------------+----------+
| field            | type     |
+------------------+----------+
| from_commit      | TEXT     |
| from_commit_date | DATETIME |
| to_commit        | TEXT     |
| to_commit_date   | DATETIME |
| diff_type        | TEXT     |
| other cols       |          |
+------------------+----------+

The remaining columns are dependent on the schema of the user table at the currently checked out branch. For every column X in your table at the currently checked out branch, there are columns in the result set named from_X and to_X with the same type as X in the current schema. The from_commit and to_commit parameters must both be specified in the query, or an error is returned.

Example Schema

Consider a simple example with a table that has one column:

+--------------+
| field | type |
+--------------+
| x     | int  |
+--------------+

Based on the table's schema above, the schema of the dolt_commit_diff_$TABLENAME will be:

+------------------+----------+
| field            | type     |
+------------------+----------+
| to_x             | int      |
| to_commit        | longtext |
| to_commit_date   | datetime |
| from_x           | int      |
| from_commit      | longtext |
| from_commit_date | datetime |
| diff_type        | varchar  |
+------------------+----------+

Query Details

Now consider the following branch structure:

      A---B---C feature
     /
D---E---F---G main

We can use the above table to represent two types of diffs: a two-point diff and a three-point diff. In a two-point diff we want to see the difference in rows between Point C and Point G.

We can also compute a three-point diff using this table. In a three-point diff we want to see how our feature branch has diverged from our common ancestor E, without including the changes from F and G on main.

The dolt_merge_base function computes the closest ancestor E between main and feature.

Additional Notes

There is one special to_commit value WORKING which can be used to see what changes are in the working set that have yet to be committed to HEAD. It is often useful to use the HASHOF() function to get the commit hash of a branch, or an ancestor commit. The above table requires both from_commit and to_commit to be filled.

dolt_diff

The dolt_diff system table shows which tables in the current database were changed in each commit reachable from the active branch's HEAD. When multiple tables are changed in a single commit, there is one row in the dolt_diff system table for each table, all with the same commit hash. Any staged or unstaged changes in the working set are included with the value WORKING for their commit_hash. After identifying the tables that changed in a commit, the dolt_diff_$TABLENAME system tables can be used to determine the data that changed in each table.

Schema

The DOLT_DIFF system table has the following columns:

+---------------+----------+
| field         | Type     |
+---------------+----------+
| commit_hash   | text     |
| table_name    | text     |
| committer     | text     |
| email         | text     |
| date          | datetime |
| message       | text     |
| data_change   | boolean  |
| schema_change | boolean  |
+---------------+----------+

Query Details

dolt_diff displays the changes from the current branch HEAD, including any working set changes. If a commit did not make any changes to tables (e.g. an empty commit), it is not included in the dolt_diff results.

Example Query

Taking the dolthub/first-hour-db database from DoltHub as our example, the following query uses the dolt_diff system table to find all commits, and the tables they changed, from the month of April 2022.

From these results, we can see there were four commits to this database in April 2022. Commits 224helo only changed the dolt_schemas table, commit 7jrvg1a changed the dolt_docs table, and commit 5jpgb0f made changes to two tables. We can also see which of these tables had changes made to their schemas vs just data.

To dig deeper into these changes, we can query the dolt_diff_$TABLE system tables specific to each of the changed tables, like this:

dolt_column_diff

The dolt_column_diff system table shows which columns and tables in the current database were changed in each commit reachable from the active branch's HEAD. When multiple columns are changed in a single commit, there is one row in the dolt_column_diff system table for each column, all with the same commit hash. Any staged changes in the working set are included with the value STAGED for their commit_hash. Any unstaged changes in the working set are included with the value WORKING for their commit_hash.

Schema

The DOLT_COLUMN_DIFF system table has the following columns

+-------------+----------+
| field       | Type     |
+-------------+----------+
| commit_hash | text     |
| table_name  | text     |
| column_name | text     |
| committer   | text     |
| email       | text     |
| date        | datetime |
| message     | text     |
| diff_type   | text     |
+-------------+----------+

Query Details

dolt_column_diff displays the changes from the current branch HEAD, including any working set changes. If a commit did not make any changes to tables (e.g. an empty commit), it is not included in the dolt_column_diff results.

Example Query

Taking the first-hour-db database from DoltHub as our example, the following query uses the dolt_column_diff system table to find commits and tables where the column name was updated.

If we narrow in on the dolt_schemas table we can count the number of commits that updated each column over the course of all our commits.

From these results, we can see that fields describing the reasons an inmate is being held are being updated far more frequently than the fields holding demographic information about inmates.

dolt_diff_$TABLENAME

For every user table named $TABLENAME, there is a read-only system table named dolt_diff_$TABLENAME that returns a list of diffs showing how rows have changed over time on the current branch. Each row in the result set represents a row that has changed between two adjacent commits on the current branch – if a row has been updated in 10 commits, then 10 individual rows are returned, showing each of the 10 individual updates.

Compared to the dolt_commit_diff_$TABLENAME system table, the dolt_diff_$TABLENAME system table focuses on how a particular row has evolved over time in the current branch's history. The major differences are that dolt_commit_diff_$TABLENAME requires specifying from_commit and to_commit, works on any commits in the database (not just the current branch), and returns a single combined diff for all changes to a row between those two commits. In the example above where a row is changed 10 times, dolt_commit_diff_$TABLENAME would only return a single row showing the diff, instead of the 10 individual deltas.

Schema

Every Dolt diff table will have the columns

+------------------+----------+
| field            | type     |
+------------------+----------+
| from_commit      | TEXT     |
| from_commit_date | DATETIME |
| to_commit        | TEXT     |
| to_commit_date   | DATETIME |
| diff_type        | TEXT     |
| other cols       |          |
+------------------+----------+

The remaining columns are dependent on the schema of the user table at the current branch. For every column X in your table at the current branch there will be columns in the result set named from_X and to_X with the same type as X.

Example Schema

For a table named states with the following schema:

+------------+--------+
| field      | type   |
+------------+--------+
| state      | TEXT   |
| population | BIGINT |
| area       | BIGINT |
+-------------+-------+

The schema for dolt_diff_states would be:

+------------------+----------+
| field            | type     |
+-----------------+-----------+
| from_state       | TEXT     |
| from_population  | BIGINT   |
| from_area        | TEXT     |
| from_commit      | TEXT     |
| from_commit_date | DATETIME |
| to_state         | TEXT     |
| to_population    | BIGINT   |
| to_area          | TEXT     |
| to_commit        | TEXT     |
| to_commit_date   | DATETIME |
| diff_type        | TEXT     |
+------------------+----------+

Query Details

A SELECT * query for a diff table will show you every change that has occurred to each row for every commit in this branch's history. Using to_commit or from_commit will limit the data to specific commits. There is one special to_commit value WORKING which can be used to see what changes are in the working set that have yet to be committed to HEAD. It is often useful to use the HASHOF() function to get the commit hash of a branch, or an ancestor commit. For example, to get the differences between the last commit and its parent you could use to_commit=HASHOF("HEAD") and from_commit=HASHOF("HEAD^").

For each row the field diff_type will be one of the values added, modified, or removed. You can filter which rows appear in the result set to one or more of those diff_type values in order to limit which types of changes will be returned.

Example Query

Taking the dolthub/us-jails database from DoltHub as our example, the following query will retrieve the jails whose total num_inmates_rated_for have changed the most between 2 versions.

Working Set Metadata System Tables

dolt_conflicts

dolt_conflicts is a system table that has a row for every table in the working set that has an unresolved merge conflict.

+---------------+-----------------+------+-----+---------+-------+
| Field         | Type            | Null | Key | Default | Extra |
+---------------+-----------------+------+-----+---------+-------+
| table         | text            | NO   | PRI |         |       |
| num_conflicts | bigint unsigned | NO   |     |         |       |
+---------------+-----------------+------+-----+---------+-------+

Query this table when resolving conflicts in a SQL session. For more information on resolving merge conflicts in SQL, see docs for the dolt_conflicts_$TABLENAME tables.

dolt_conflicts_$TABLENAME

For each table $TABLENAME in conflict after a merge, there is a corresponding system table named dolt_conflicts_$TABLENAME. The schema of each such table contains three columns for each column in the actual table, representing each row in conflict for each of ours, theirs, and base values.

Consider a table mytable with this schema:

+-------+------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+------+------+-----+---------+-------+
| a     | int  | NO   | PRI |         |       |
| b     | int  | YES  |     |         |       |
+-------+------+------+-----+---------+-------+

If we attempt a merge that creates conflicts in this table, the dynamically generated table will show the details of the conflict:

mydb> select * from dolt_conflicts_mytable;
+----------------------------------+--------+--------+-------+-------+---------------+---------+---------+-----------------+------------------------+
| from_root_ish                    | base_a | base_b | our_a | our_b | our_diff_type | their_a | their_b | their_diff_type | dolt_conflict_id       |
+----------------------------------+--------+--------+-------+-------+---------------+---------+---------+-----------------+------------------------+
| gip4h957r8k07c9414lkp3sqe7rh9an6 | NULL   | NULL   | 3     | 3     | added         | 3       | 1       | added           | hWDLmYufTrm+eVjFSVzPWw |
| gip4h957r8k07c9414lkp3sqe7rh9an6 | NULL   | NULL   | 4     | 4     | added         | 4       | 2       | added           | gi2p1YbSwu8oUV/WRSpr3Q |
+----------------------------------+--------+--------+-------+-------+---------------+---------+---------+-----------------+------------------------+

The table has a single row for every row that conflicts in the table. Each column is listed three times, once for the base, once for the ours value, and once for the theirs value. Additionally, the our_diff_type and their_diff_type columns indicate whether the row was "added", "modified", or "removed" in the corresponding branch. The dolt_conflict_id column is unique for each row, and can be used to identify the specific conflict when writing automated conflict resolution applications. Finally, the first column, from_root_ish is the ID of the database root at the time of the merge. User code generally ignores this column.

To simplify, you can query for just the columns you are interested in:

mydb> select dolt_conflict_id, base_a, base_b, our_a, our_b, their_a, their_b from dolt_conflicts_mytable;
+------------------------+--------+--------+-------+-------+---------+---------+
| dolt_conflict_id       | base_a | base_b | our_a | our_b | their_a | their_b |
+------------------------+--------+--------+-------+-------+---------+---------+
| hWDLmYufTrm+eVjFSVzPWw | NULL   | NULL   | 3     | 3     | 3       | 1       |
| gi2p1YbSwu8oUV/WRSpr3Q | NULL   | NULL   | 4     | 4     | 4       | 2       |
+------------------------+--------+--------+-------+-------+---------+---------+

To mark conflicts as resolved, delete them from the corresponding table. To effectively keep all our values, I would simply run:

mydb> delete from dolt_conflicts_mytable;

If I wanted to keep all their values, I would first run this statement:

mydb> replace into mytable (select their_a, their_b from dolt_conflicts_mytable);

For convenience, you can also modify the our_ columns of the dolt_conflicts_mytable to update the corresponding row in mytable. The above replace statement can be rewritten as:

mydb> update dolt_conflicts_mytable set our_a = their_a, our_b = their_b;

And of course you can use any combination of ours, theirs and base rows in these statements.

Notes

  • Updates made to the our_ columns are applied to the original table using the primary key (or keyless hash). If the row does not exist, it will be inserted. Updates made to our_ columns will never delete a row, however.

  • dolt_conflict_id is a unique identifier for the conflict. It is particularly useful when writing software that needs to resolve conflicts automatically.

  • from_root_ish is the commit hash of the "from branch" of the merge. This hash can be used to identify which merge produced a conflict, since conflicts can accumulate across merges.

dolt_schema_conflicts

dolt_schema_conflicts is a system table that has a row for every table in the working set that has an unresolved schema conflict.

> SELECT table_name, description, base_schema, our_schema, their_schema FROM dolt_schema_conflicts;
+------------+--------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------+
| table_name | description                          | base_schema                                                       | our_schema                                                        | their_schema                                                      |
+------------+--------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------+
| people     | different column definitions for our | CREATE TABLE `people` (                                           | CREATE TABLE `people` (                                           | CREATE TABLE `people` (                                           |
|            | column age and their column age      |   `id` int NOT NULL,                                              |   `id` int NOT NULL,                                              |   `id` int NOT NULL,                                              |
|            |                                      |   `last_name` varchar(120),                                       |   `last_name` varchar(120),                                       |   `last_name` varchar(120),                                       |
|            |                                      |   `first_name` varchar(120),                                      |   `first_name` varchar(120),                                      |   `first_name` varchar(120),                                      |
|            |                                      |   `birthday` datetime(6),                                         |   `birthday` datetime(6),                                         |   `birthday` datetime(6),                                         |
|            |                                      |   `age` int DEFAULT '0',                                          |   `age` float,                                                    |   `age` bigint,                                                   |
|            |                                      |   PRIMARY KEY (`id`)                                              |   PRIMARY KEY (`id`)                                              |   PRIMARY KEY (`id`)                                              |
|            |                                      | ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_bin; | ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_bin; | ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_bin; |
+------------+--------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------+

Query this table when resolving schema conflicts in a SQL session. For more information on resolving schema conflicts during merge, see the docs on conflicts.

dolt_merge_status

The dolt_merge_status system table tells a user if a merge is active. It has the following schema:

CREATE TABLE `dolt_merge_status` (
  -- Whether a merge is currently active or not
  `is_merging` tinyint NOT NULL,
  -- The commit spec that was used to initiate the merge
  `source` text,
  -- The commit that the commit spec resolved to at the time of merge
  `source_commit` text,
  -- The target destination working set
  `target` text,
  -- A list of tables that have conflicts or constraint violations
  `unmerged_tables` text
)

Example

Let's create a simple conflict:

dolt sql -q "CREATE TABLE t (a INT PRIMARY KEY, b INT);"
dolt add .
dolt commit -am "base"

dolt checkout -b right
dolt sql <<SQL
ALTER TABLE t ADD c INT;
INSERT INTO t VALUES (1, 2, 1);
SQL
dolt commit -am "right"

dolt checkout main
dolt sql -q "INSERT INTO t values (1, 3);"
dolt commit -am "left"

dolt merge right

Output of SELECT * from dolt_merge_status;:

+------------+--------+----------------------------------+-----------------+-----------------+
| is_merging | source | source_commit                    | target          | unmerged_tables |
+------------+--------+----------------------------------+-----------------+-----------------+
| true       | right  | fbghslue1k9cfgbi00ti4r8417frgbca | refs/heads/main | t               |
+------------+--------+----------------------------------+-----------------+-----------------+

dolt_stashes

The dolt_stashes system table returns information about all stashes in the current database.

The dolt_stashes table is read-only. Use the dolt_stash() stored procedure or the dolt stash cli functions to create, apply, or delete stashes.

Schema

+----------------+------+------+-----+
| Field          | Type | Null | Key |
+----------------+------+------+-----+
| name           | text | NO   |     |
| stash_id       | text | NO   |     |
| branch         | text | NO   |     |
| hash           | text | NO   |     |
| commit_message | text | NO   |     |
+----------------+------+------+-----+

Fields

  • name: The name of the stash entry

  • stash_id: The unique identifier for the stash (e.g., "stash@{0}")

  • branch: The branch where the stash was created

  • hash: The commit hash of the stashed changes

  • commit_message: Message for the commit the stash was created on

Example Query

SELECT * 
FROM dolt_stashes
WHERE name = 'myStash';
+---------+------------+--------+----------------------------------+------------------+
| name    | stash_id   | branch | hash                             | commit_message   |
+---------+------------+--------+----------------------------------+------------------+
| myStash | stash@{0}  |  main  | pnpq4p07977jjbpkg6ojj2mpjp2kru9r | Created a table  |
+---------+------------+--------+----------------------------------+------------------+

dolt_status

dolt_status returns the status of the database session, analogous to running dolt status from the command line.

Schema

+------------+---------+------+-----+
| Field      | Type    | Null | Key |
+------------+---------+------+-----+
| table_name | text    | NO   | PRI |
| staged     | tinyint | NO   | PRI |
| status     | text    | NO   | PRI |
+------------+---------+------+-----+

Example Query

SELECT *
FROM dolt_status
WHERE staged=false;
+------------+--------+-----------+
| table_name | staged | status    |
+------------+--------+-----------+
| one_pk     | false  | new table |
+------------+--------+-----------+

dolt_workspace_$TABLENAME

This system table shows you which rows have been changed in your workspace and if they are staged. It is the union of rows changed from HEAD to STAGED, and STAGED to WORKING. Any table listed in dolt_status table will have a non-empty corresponding dolt_workspace_$TABLENAME table. Changes listed are all relative to the HEAD of the current branch.

These tables can be modified in order to update what changes are staged for commit. Workspace review

Schema

The schema of the source table is going to affect the schema of the workspace table. The first three column are always the same, then the schema of the source table is used to create "to_" and "from_" columns.

Each row in the dolt_workspace_$TABLENAME corresponds to a single row update in the table.

+------------------+----------+
| field            | type     |
+------------------+----------+
| id               | int      |
| staged           | bool     |
| diff_type        | varchar  |
| to_x             | ...      |
| to_y             | ...      |
| from_x           | ...      |
| from_y           | ...      |
+------------------+----------+

The staged column will be TRUE when the changes are going to be committed on the next call to dolt_commit(). Changes which have staged = FALSE are present in your workspace which means all queries in your session contain them but they will not be recorded in the event that dolt_commit() is executed.

There are two ways you can alter the state of your workspace using these tables.

  1. The staged column can be toggled for any row. If changing from false to true, the row values will be moved to staging. If there are already staged changes for that row, they will be overwritten. If changing from true to false, the row values will be unstaged. If there are other changes in the workspace for that row, the workspace change will be preserved and the staged change will be dropped.

  2. Any row which has staged = FALSE can be deleted. This will result in reverting the change to the row in the source table.

Example Query

SELECT *
FROM dolt_workspace_mytable
WHERE staged=false
+----+--------+-----------+-------+----------+---------+------------+
| id | staged | diff_type | to_id | to_value | from_id | from_value |
+----+--------+-----------+-------+----------+---------+------------+
| 0  | false  | modified  | 3     | 44       | 3       | 31         |
| 1  | false  | modified  | 4     | 68       | 4       | 1          |
| 2  | false  | modified  | 9     | 47       | 9       | 59         |
+----+--------+-----------+-------+----------+---------+------------+
3 rows in set (0.00 sec)
UPDATE dolt_workspace_mytable SET staged = TRUE WHERE to_id = 3;
CALL dolt_commit("-m", "Added row id 3 in my table");

Notes

The dolt_workspace_$TABLENAME tables are generated based on the session state when inspected, so they can not be considered stable on a branch which has multiple editors.

Constraint Violation System Tables

dolt_constraint_violations

The dolt_constraint_violations system table contains one row for every table that has a constraint violation introduced by a merge. Dolt enforces constraints (such as foreign keys) during normal SQL operations, but it's possible that a merge puts one or more tables in a state where constraints no longer hold. For example, a row deleted in the merge base could be referenced via a foreign key constraint by an added row in the merged commit. Use dolt_constraint_violations to discover such violations.

Schema

+----------------+-----------------+------+-----+---------+-------+
| Field          | Type            | Null | Key | Default | Extra |
+----------------+-----------------+------+-----+---------+-------+
| table          | text            | NO   | PRI |         |       |
| num_violations | bigint unsigned | NO   |     |         |       |
+----------------+-----------------+------+-----+---------+-------+

dolt_constraint_violations_$TABLENAME

For each table $TABLENAME with a constraint violation after a merge, there is a corresponding system table named dolt_constraint_violations_$TABLENAME. Each row in the table represents a constraint violation that must be resolved via INSERT, UPDATE, or DELETE statements. Resolve each constraint violation before committing the result of the merge that introduced them.

Schema

For a hypothetical table a with the following schema:

+-------+------------+------+-----+---------+-------+
| Field | Type       | Null | Key | Default | Extra |
+-------+------------+------+-----+---------+-------+
| x     | bigint     | NO   | PRI |         |       |
| y     | varchar(1) | YES  |     |         |       |
+-------+------------+------+-----+---------+-------+

dolt_constraint_violations_a will have the following schema:

+----------------+------------------------------------------------------------------+------+-----+---------+-------+
| Field          | Type                                                             | Null | Key | Default | Extra |
+----------------+------------------------------------------------------------------+------+-----+---------+-------+
| from_root_ish  | varchar(1023)                                                    | YES  |     |         |       |
| violation_type | enum('foreign key','unique index','check constraint','not null') | NO   | PRI |         |       |
| x              | bigint                                                           | NO   | PRI |         |       |
| y              | varchar(1)                                                       | YES  |     |         |       |
| violation_info | json                                                             | YES  |     |         |       |
+----------------+------------------------------------------------------------------+------+-----+---------+-------+

Each row in the table represents a row in the primary table that is in violation of one or more constraint violations. The violation_info field is a JSON payload describing the violation. The payload varies depending on the type of constraint violation recorded.

For foreign key violations:

{
  "ForeignKey": "key_name",
  "Table": "myTable",
  "Columns": ["col1", "col2"],
  "Index": "myIdx",
  "OnDelete": "RESTRICT",
  "OnUpdate": "RESTRICT",
  "ReferencedColumns": ["col3", "col4"],
  "ReferencedIndex": "myIdx2",
  "ReferencedTable": "refTable"
}

For unique constraints:

{
  "Name": "constraint_name",
  "Columns": ["col1", "col2"]
}

For not null constraints:

{
  "Columns": ["col1", "col2"]
}

For check constraints:

{
  "Name": "constraint_name",
  "Expression": "(col1 > 0)"
}

As with dolt_conflicts, delete rows from the corresponding dolt_constraint_violations table to signal to dolt that you have resolved any such violations before committing.

Configuration Tables

Configuration Tables can be staged and versioned just like user tables. They always exist, even in an empty database.

dolt_ignore

dolt_ignore stores a list of "table name patterns", and a boolean flag for each pattern indicating whether tables that match the patterns should not be staged for commit.

This only affects the staging of new tables. Tables that have already been staged or committed are not affected the contents of dolt_ignore, and changes to those tables can still be staged.

Schema

+------------+---------+------+-----+
| Field      | Type    | Null | Key |
+------------+---------+------+-----+
| pattern    | text    | NO   | PRI |
| ignored    | tinyint | NO   |     |
+------------+---------+------+-----+

Notes

The format of patterns is a simplified version of gitignore’s patterns:

  • An asterisk "*" or ampersand "%" matches any number of characters.

  • The character "?" matches any one character.

  • All other characters match exactly.

If a table name matches multiple patterns with different values for ignored, the most specific pattern is chosen (a pattern A is more specific than a pattern B if all names that match A also match pattern B, but not vice versa.) If no pattern is most specific, then attempting to stage that table will result in an error.

Tables that match patterns in dolt_ignore can be force-committed by passing the --force flag to dolt add or CALL dolt_add.

dolt diff won't display ignored tables, and dolt show won't display ignored tables unless the additional --ignored flag is passed.

Example Query

INSERT INTO dolt_ignore VALUES ("generated_*", true), ("generated_exception", false);
CREATE TABLE foo (pk int);
CREATE TABLE generated_foo (pk int);
CREATE TABLE generated_exception (pk int);
CALL dolt_add("-A");
SELECT *
FROM dolt_status
WHERE staged=true;
+---------------------+--------+-----------+
| table_name          | staged | status    |
+---------------------+--------+-----------+
| foo                 | true   | new table |
| generated_exception | true   | new table |
+---------------------+--------+-----------+

dolt_tests

dolt_tests stores test definitions that can be executed using the DOLT_TEST_RUN() table function. Tests define SQL queries with assertions about their expected results, providing a way to validate database behavior and catch regressions.

Schema

+----------------------+------+------+-----+
| Field                | Type | Null | Key |
+----------------------+------+------+-----+
| test_name            | text | NO   | PRI |
| test_group           | text | YES  |     |
| test_query           | text | NO   |     |
| assertion_type       | text | NO   |     |
| assertion_comparator | text | NO   |     |
| assertion_value      | text | NO   |     |
+----------------------+------+------+-----+

Notes

Test queries must be read-only (no INSERT, UPDATE, DELETE, or DDL statements) and can only contain a single SQL statement.

There are three types of assertions available:

  • expected_rows: Asserts on the number of rows returned by the query. The assertion_value should be an integer.

  • expected_columns: Asserts on the number of columns returned by the query. The assertion_value should be an integer.

  • expected_single_value: Asserts on the value of a single cell. The query must return exactly one row and one column. The assertion_value is compared against the returned value.

The assertion_comparator field supports the following comparison operators: ==, !=, <, >, <=, >=.

Example Queries

Create a test that verifies a table has the expected number of rows:

INSERT INTO dolt_tests VALUES 
('check_user_count', 'users', 'SELECT * FROM users', 'expected_rows', '==', '10');

Create a test that validates a specific calculated value:

INSERT INTO dolt_tests VALUES 
('total_revenue', 'finance', 'SELECT SUM(amount) FROM sales', 'expected_single_value', '>=', '100000');

Rebasing Tables

dolt_rebase

dolt_rebase is only present while an interactive rebase is in progress, and only on the branch where the rebase is being executed. For example, when rebasing the feature1 branch, the rebase will be executed on the dolt_rebase_feature1 branch, and the dolt_rebase system table will exist on that branch while the rebase is in-progress. The dolt_rebase system table starts off with the default rebase plan, which is to pick all of the commits identified for the rebase. Users can adjust the rebase plan by updating the dolt_rebase table to change the rebase action, reword a commit message, or even add new rows with additional commits to be applied as part of the rebase. For more details about rebasing, see the dolt_rebase() stored procedure.

Schema

+----------------+---------------------------------------------------+
| Field          | Type                                              |
+----------------+---------------------------------------------------+
| rebase_order   | DECIMAL(6,2)                                      |
| action         | ENUM('pick', 'drop', 'reword', 'squash', 'fixup') |
| commit_hash    | TEXT                                              |
| commit_message | TEXT                                              |
+----------------+---------------------------------------------------+

The action field can take one of the following rebase actions:

  • pick - apply a commit as is and keep its commit message.

  • drop - do not apply a commit. The row in the dolt_rebase table can also be deleted to drop a commit from the rebase plan.

  • reword - apply a commit, and use the updated commit message from the commit_message field in the dolt_rebase table for its commit message. Note that if you edit the commit_message but do not use the reword action, the original commit message will still be used.

  • squash - apply a commit, but include its changes in the previous commit instead of creating a new commit. The commit message of the previous commit will be altered to include the previous commit message as well as the commit message from the squashed commit. Note that the rebase plan MUST include a pick or reword action in the plan before a squash action.

  • fixup - apply a commit, but include its changes in the previous commit instead of creating a new commit. The commit message of the previous commit will NOT be changed, and the commit message from the fixup commit will be discarded. Note that the rebase plan MUST include a pick or reword action in the plan before a fixup action.

Example Queries

To squash all commits into a single commit and include the commit messages from all commits, the following query can be used:

update dolt_rebase set action = 'squash' where rebase_order > 1;

To reword a commit with commit hash '123aef456f', be sure to set the action to reword and to update the commit_message field:

update dolt_rebase set action = 'reword', commit_message = 'here is my new message' where commit_hash = '123aef456f';

To drop the second commit in the rebase plan, you can use the drop action:

update dolt_rebase set action = 'drop' where rebase_order = 2;

Or you can simply delete that row from the dolt_rebase table:

delete from dolt_rebase where rebase_order = 2;
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