Generate a random sample of rows from a relational database that preserves referential integrity - so long as constraints are defined, all parent rows will exist for child rows.
Good for creating test/development databases from production. It's slow, but how often do you need to generate a test/development database?
Usage:
rdbms-subsetter <source SQLAlchemy connection string> <destination connection string> <fraction of rows to use>
Example:
rdbms-subsetter postgresql://:@/bigdb postgresql://:@/littledb 0.05
Valid SQLAlchemy connection strings are described here.
rdbms-subsetter
promises that each child row will have whatever parent rows are
required by its foreign keys. It will also try to include most child rows belonging
to each parent row (up to the supplied --children
parameter, default 3 each), but it
can't make any promises. (Demanding all children can lead to infinite propagation in
thoroughly interlinked databases, as every child record demands new parent records,
which demand new child records, which demand new parent records...
so increase --children
with caution.)
When row numbers in your tables vary wildly (tens to billions, for example),
consider using the -l
flag, which sets row number targets
by a logarithmic formula.
When -l
is set, if f
is the fraction specified,
and the original table has n
rows,
then each new table's row target will be:
math.pow(10, math.log10(n)*f)
A fraction of 0.5
seems to produce good results, converting 10 rows to 3,
1,000,000 to 1,000, and 1,000,000,000 to 31,622.
Rows are selected randomly, but for tables with a single primary key column, you
can force rdbms-subsetter to include specific rows (and their dependencies) with
force=<tablename>:<primary key value>
. The children, grandchildren, etc. of
these rows
are exempted from the --children
limit.
rdbms-subsetter
only performs the INSERTS; it's your responsibility to set
up the target database first, with its foreign key constraints. The easiest
way to do this is with your RDBMS's dump utility. For example, for PostgreSQL,
pg_dump --schema-only -f schemadump.sql bigdb createdb littledb psql -f schemadump.sql littledb
Rows are taken from the schema visible by default to your
database connection. You can also include rows from non-default schemas
with the --schema=<name>
parameter (which can be used multiple times).
Currently the target database must contain the corresponding tables in its own
schema of the same name (moving between schemas of different names is not yet
supported).
You can restrict the tables included in the sample via the --table
(-t
) and --exclude-table
(-T
) parameters (which can be used
multiple times). These parameters take a table name or pattern with wildcards
(*
), and supports both qualified names (i.e. schema.table
) and simple
names. When both -t
and -T
are given, the behavior is to include just
the tables that match at least one -t
switch, but no -T
switches.
When target db write buffering is enabled (which it is by default), subset extraction for complex schemas that have tangled foreign key relationships may fail. To disable write buffering, set the buffer parameter to 0:
rdbms-subsetter postgresql://:@/bigdb postgresql://:@/littledb 0.05 -b 0
If you need to honor relationships that aren't actually defined as foreign-key
constraints in the database - for example, if you are using MySQL MyISAM
and can't define constraints - you can specify a
configuration file with --config
. The config file should specify constraints
in JSON. For example,
- {
- "constraints": {
- "(child_table_name)": [
- {
- "referred_schema": null, "referred_table": "(name of parent table)", "referred_columns": ["(constraint col 1 in parent)", "(constraint col 2 in parent)",], "constrained_columns": ["(constrained col 1 in child)", "(constrained col 2 in child)",],
}
],
}, "tables": [ "SCHEMA1.TABLE1", "SCHEMA2.TABLE2" ], "schemas": [ "SCHEMA1", "SCHEMA2" ]
}
Optionally, you can qualify child_table_name
, i.e.
schema_name.child_table_name
. Cross-schema constraints are also supported.
rdbms-subsetter
treats these constraints like real foreign keys and fetches
parent and child rows as described above.
tables
and schemas
are optional.
tables
are merged with the --table
elements passed on commandline.
schemas
are merged with the --schema
elements passed on commandline.
If you provide a python module with appropriate signal handling functions, and specify that module
when calling the script like --import=my.signals.signal_handlers
, then any signal handlers that you
have registered in your module will be called when the corresponding signals are sent during
the DB subsetting process.
At the moment, the only signal is subsetter.SIGNAL_ROW_ADDED
.
An example signal handling module:
from blinker import signal import subsetter row_added_signal = signal(subsetter.SIGNAL_ROW_ADDED) @row_added_signal.connect def row_added(source_db, **kwargs): print("row_added called with source db: {}, and kwargs: {}".format(source_db, kwargs))
This signal will be sent when a new row has been selected for adding to the target database. The associated signal handler should have the following signature:
def row_added(source_db, **kwargs):
source_db
is a subsetter.Db
instance.
kwargs
contains:
target_db
: asubsetter.Db
instance.source_row
: ansqlalchemy.engine.RowProxy
with the values from the row that will be inserted.target_table
: ansqlalchemy.Table
.prioritized
: abool
representing whether of not all child, grandchild, etc. rows should be included.
pip install rdbms-subsetter
Then the DB-API2 module for your RDBMS; for example, for PostgreSQL,
pip install psycopg2
Will consume memory roughly equal to the size of the extracted database. (Not the size of the source database!)
https://github.com/18F/rdbms-subsetter