Стратегия Incremental Batch
Bases: BatchHWMStrategy
Incremental batch strategy for :ref:db-reader.
.. note::
Cannot be used with :ref:`file-downloader`
Same as :obj:IncrementalStrategy <onetl.strategy.incremental_strategy.IncrementalStrategy>,
but reads data from the source in sequential batches (1..N) like:
.. code:: sql
1: SELECT id, data
FROM public.mydata
WHERE id > 1000 AND id <= 1100; -- previous HWM value is 1000, step is 100
2: WHERE id > 1100 AND id <= 1200; -- + step
3: WHERE id > 1200 AND id <= 1200; -- + step
N: WHERE id > 1300 AND id <= 1400; -- until stop
This allows to use less CPU and RAM than reading all the data in the one batch, but takes proportionally more time.
.. warning::
Unlike :obj:`SnapshotBatchStrategy <onetl.strategy.snapshot_strategy.SnapshotBatchStrategy>`,
it **saves** current HWM value after **each batch** into :ref:`HWM Store <hwm>`.
So if code inside the context manager raised an exception, like:
.. code:: python
with IncrementalBatchStrategy() as batches:
for _ in batches:
df = reader.run() # something went wrong here
writer.run(df) # or here
# or here...
DBReader will **NOT** update HWM in HWM Store for the failed batch.
All of that allows to resume reading process from the *last successful batch*.
.. warning::
Not every :ref:`DB connection <db-connections>`
supports batch strategy. For example, Kafka connection doesn't support it.
Make sure the connection you use is compatible with the IncrementalBatchStrategy.
.. versionadded:: 0.1.0
Parameters
step : Any
Step size used for generating batch SQL queries like:
.. code:: sql
SELECT id, data
FROM public.mydata
WHERE id > 1000 AND id <= 1100; -- 1000 is previous HWM value, step is 100
.. note::
Step defines a range of values will be fetched by each batch. This is **not**
a number of rows, it depends on a table content and value distribution across the rows.
.. note::
``step`` value will be added to the HWM, so it should have a proper type.
For example, for ``TIMESTAMP`` column ``step`` type should be :obj:`datetime.timedelta`, not :obj:`int`
stop : Any, default: None
If passed, the value will be used for generating WHERE clauses with ``hwm.expression`` filter,
as a stop value for the last batch.
If not set, the value is determined by a separated query:
.. code:: sql
SELECT MAX(id) as stop
FROM public.mydata
WHERE id > 1000; -- 1000 is previous HWM value (if any)
.. note::
``stop`` should be the same type as ``hwm.expression`` value,
e.g. :obj:`datetime.datetime` for ``TIMESTAMP`` column, :obj:`datetime.date` for ``DATE``, and so on
offset : Any, default: None
If passed, the offset value will be used to read rows which appeared in the source after the previous read.
For example, previous incremental run returned rows:
.. code::
898
899
900
1000
Current HWM value is 1000.
But since then few more rows appeared in the source:
.. code::
898
899
900
901 # new
902 # new
...
999 # new
1000
and you need to read them too.
So you can set ``offset=100``, so the first batch of a next incremental run will look like:
.. code:: sql
SELECT id, data
FROM public.mydata
WHERE id > 900 AND id <= 1000; -- 900 = 1000 - 100 = HWM - offset
and return rows from 901 (**not** 900) to **1000** (duplicate).
.. warning::
This can lead to reading duplicated values from the table.
You probably need additional deduplication step to handle them
.. note::
``offset`` value will be subtracted from the HWM, so it should have a proper type.
For example, for ``TIMESTAMP`` column ``offset`` type should be :obj:`datetime.timedelta`, not :obj:`int`
Examples
.. tabs::
.. tab:: IncrementalBatch run
.. code:: python
from onetl.db import DBReader, DBWriter
from onetl.strategy import IncrementalBatchStrategy
reader = DBReader(
connection=postgres,
source="public.mydata",
columns=["id", "data"],
hwm=DBReader.AutoDetectHWM(name="some_hwm_name", expression="id"),
)
writer = DBWriter(connection=hive, target="db.newtable")
with IncrementalBatchStrategy(step=100) as batches:
for _ in batches:
df = reader.run()
writer.run(df)
.. code:: sql
-- previous HWM value was 1000
-- each batch (1..N) will perform a query which return some part of input data
1: SELECT id, data
FROM public.mydata
WHERE id > 1100 AND id <= 1200; --- from HWM to HWM+step (EXCLUDING first row)
2: WHERE id > 1200 AND id <= 1300; -- + step
N: WHERE id > 1300 AND id <= 1400; -- until max value of HWM column
.. tab:: IncrementalBatch run with ``stop`` value
.. code:: python
...
with IncrementalBatchStrategy(step=100, stop=2000) as batches:
for _ in batches:
df = reader.run()
writer.run(df)
.. code:: sql
-- previous HWM value was 1000
-- each batch (1..N) will perform a query which return some part of input data
1: SELECT id, data
FROM public.mydata
WHERE id > 1000 AND id <= 1100; --- from HWM to HWM+step (EXCLUDING first row)
2: WHERE id > 1100 AND id <= 1200; -- + step
...
N: WHERE id > 1900 AND id <= 2000; -- until stop
.. tab:: IncrementalBatch run with ``offset`` value
.. code:: python
...
with IncrementalBatchStrategy(step=100, offset=100) as batches:
for _ in batches:
df = reader.run()
writer.run(df)
.. code:: sql
-- previous HWM value was 1000
-- each batch (1..N) will perform a query which return some part of input data
1: SELECT id, data
FROM public.mydata
WHERE id > 900 AND id <= 1000; --- from HWM-offset to HWM-offset+step (EXCLUDING first row)
2: WHERE id > 1000 AND id <= 1100; -- + step
3: WHERE id > 1100 AND id <= 1200; -- + step
...
N: WHERE id > 1300 AND id <= 1400; -- until max value of HWM column
.. tab:: IncrementalBatch run with all possible options
.. code:: python
...
with IncrementalBatchStrategy(
step=100,
stop=2000,
offset=100,
) as batches:
for _ in batches:
df = reader.run()
writer.run(df)
.. code:: sql
-- previous HWM value was 1000
-- each batch (1..N) will perform a query which return some part of input data
1: SELECT id, data
FROM public.mydata
WHERE id > 900 AND id <= 1000; --- from HWM-offset to HWM-offset+step (EXCLUDING first row)
2: WHERE id > 1000 AND id <= 1100; -- + step
3: WHERE id > 1100 AND id <= 1200; -- + step
...
N: WHERE id > 1900 AND id <= 2000; -- until stop
.. tab:: IncrementalBatch run over non-integer column
``hwm.expression``, ``offset`` and ``stop`` can be a date or datetime, not only integer:
.. code:: python
from onetl.db import DBReader, DBWriter
from datetime import date, timedelta
reader = DBReader(
connection=postgres,
source="public.mydata",
columns=["business_dt", "data"],
hwm=DBReader.AutoDetectHWM(name="some_hwm_name", expression="business_dt"),
)
writer = DBWriter(connection=hive, target="db.newtable")
with IncrementalBatchStrategy(
step=timedelta(days=5),
stop=date("2021-01-31"),
offset=timedelta(days=1),
) as batches:
for _ in batches:
df = reader.run()
writer.run(df)
.. code:: sql
-- previous HWM value was '2021-01-10'
-- each batch (1..N) will perform a query which return some part of input data
1: SELECT business_dt, data
FROM public.mydata
WHERE business_dt > CAST('2021-01-09' AS DATE) -- from HWM-offset (EXCLUDING first row)
AND business_dt <= CAST('2021-01-14' AS DATE); -- to HWM-offset+step
2: WHERE business_dt > CAST('2021-01-14' AS DATE) -- + step
AND business_dt <= CAST('2021-01-19' AS DATE);
3: WHERE business_dt > CAST('2021-01-19' AS DATE) -- + step
AND business_dt <= CAST('2021-01-24' AS DATE);
...
N: WHERE business_dt > CAST('2021-01-29' AS DATE)
AND business_dt <= CAST('2021-01-31' AS DATE); -- until stop
Source code in onetl/strategy/incremental_strategy.py
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