Added more docs

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M1ha 2020-02-07 13:05:19 +05:00
parent 5cb43ca6cd
commit 7d2d94336c
10 changed files with 199 additions and 21 deletions

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@ -38,7 +38,7 @@ A database alias to use in [QuerySets](queries.md) if direct [using](routing.md#
### CLICKHOUSE_SYNC_STORAGE ### CLICKHOUSE_SYNC_STORAGE
Defaults to: `'django_clickhouse.storages.RedisStorage'` Defaults to: `'django_clickhouse.storages.RedisStorage'`
An intermediate storage class to use. Can be a string or class. [More info about storages](storages.md). An [intermediate storage](storages.md) class to use. Can be a string or class.
### CLICKHOUSE_REDIS_CONFIG ### CLICKHOUSE_REDIS_CONFIG
Default to: `None` Default to: `None`
@ -57,11 +57,11 @@ CLICKHOUSE_REDIS_CONFIG = {
### CLICKHOUSE_SYNC_BATCH_SIZE ### CLICKHOUSE_SYNC_BATCH_SIZE
Defaults to: `10000` Defaults to: `10000`
Maximum number of operations, fetched by sync process from intermediate storage per sync round. Maximum number of operations, fetched by sync process from [intermediate storage](storages.md) per [sync](sync.md)) round.
### CLICKHOUSE_SYNC_DELAY ### CLICKHOUSE_SYNC_DELAY
Defaults to: `5` Defaults to: `5`
A delay in seconds between two sync rounds start. A delay in seconds between two [sync](synchronization.md) rounds start.
### CLICKHOUSE_MODELS_MODULE ### CLICKHOUSE_MODELS_MODULE
Defaults to: `'clickhouse_models'` Defaults to: `'clickhouse_models'`

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@ -22,6 +22,9 @@ secondary = connections['secondary']
db_link = connections['default'] db_link = connections['default']
``` ```
You can also get database objects from [QuerySet](queries.md) and [ClickHouseModel](models.md) instances by calling `get_database(for_write: bool = False)` method.
This database may differ, depending on [routing](routing.md#router) you use.
## Database object ## Database object
Database class is based on [infi.clickhouse_orm Database object](https://github.com/Infinidat/infi.clickhouse_orm/blob/develop/docs/models_and_databases.md#models-and-databases), Database class is based on [infi.clickhouse_orm Database object](https://github.com/Infinidat/infi.clickhouse_orm/blob/develop/docs/models_and_databases.md#models-and-databases),
but extends it with some extra attributes and methods: but extends it with some extra attributes and methods:
@ -31,10 +34,4 @@ I expect this library [migration system](migrations.md) to be used.
Direct database migration will lead to migration information errors. Direct database migration will lead to migration information errors.
### `insert_tuples` and `select_tuples` methods ### `insert_tuples` and `select_tuples` methods
[infi.clickhouse_orm](https://github.com/Infinidat/infi.clickhouse_orm) store data rows in Model objects. Methods to work with [ClickHouseModel namedtuples](models.md#clickhousemodel-namedtuple-form).
It works well on hundreds of records.
But when you sync 100k records in a batch, initializing 100k model instances will be slow.
Too optimize this process `ClickHouseModel` class have `get_tuple_class()` method.
It generates a [namedtuple](https://docs.python.org/3/library/collections.html#collections.namedtuple) class,
with same data fields a model has.
Initializing such tuples takes much less time, then initializing Model objects.

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@ -6,7 +6,7 @@
* [Requirements](basic_information.md#requirements) * [Requirements](basic_information.md#requirements)
* [Installation](basic_information.md#installation) * [Installation](basic_information.md#installation)
* [Design motivation](motivation.md) * [Design motivation](motivation.md)
* Usage * [Usage](overview.md)
* [Overview](overview.md) * [Overview](overview.md)
* [Models](models.md) * [Models](models.md)
* [DjangoModel](models.md#DjangoModel) * [DjangoModel](models.md#DjangoModel)

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@ -109,6 +109,15 @@ class MyMultiModel(ClickHouseMultiModel):
sub_models = [AgeData, HeightData] sub_models = [AgeData, HeightData]
``` ```
## ClickHouseModel namedtuple form
[infi.clickhouse_orm](https://github.com/Infinidat/infi.clickhouse_orm) stores data rows in special Model objects.
It works well on hundreds of records.
But when you sync 100k records in a batch, initializing 100k model instances will be slow.
Too optimize this process `ClickHouseModel` class have `get_tuple_class()` method.
It generates a [namedtuple](https://docs.python.org/3/library/collections.html#collections.namedtuple) class,
with same data fields a model has.
Initializing such tuples takes much less time, then initializing Model objects.
## Engines ## Engines
Engine is a way of storing, indexing, replicating and sorting data ClickHouse ([docs](https://clickhouse.yandex/docs/en/operations/table_engines/)). Engine is a way of storing, indexing, replicating and sorting data ClickHouse ([docs](https://clickhouse.yandex/docs/en/operations/table_engines/)).
Engine system is based on [infi.clickhouse_orm engine system](https://github.com/Infinidat/infi.clickhouse_orm/blob/develop/docs/table_engines.md#table-engines). Engine system is based on [infi.clickhouse_orm engine system](https://github.com/Infinidat/infi.clickhouse_orm/blob/develop/docs/table_engines.md#table-engines).
@ -120,3 +129,25 @@ Currently supported engines (with all infi functionality, [more info](https://gi
* `ReplacingMergeTree` * `ReplacingMergeTree`
* `SummingMergeTree` * `SummingMergeTree`
* `CollapsingMergeTree` * `CollapsingMergeTree`
## Serializers
Serializer is a class which translates django model instances to [namedtuples, inserted into ClickHouse](#clickhousemodel-namedtuple-form).
`django_clickhouse.serializers.Django2ClickHouseModelSerializer` is used by default in all models.
All serializers must inherit this class.
Serializer must implement next interface:
```python
from django_clickhouse.serializers import Django2ClickHouseModelSerializer
from django.db.models import Model as DjangoModel
from typing import *
class CustomSerializer(Django2ClickHouseModelSerializer):
def __init__(self, model_cls: Type['ClickHouseModel'], fields: Optional[Iterable[str]] = None,
exclude_fields: Optional[Iterable[str]] = None, writable: bool = False,
defaults: Optional[dict] = None) -> None:
super().__init__(model_cls, fields=fields, exclude_fields=exclude_fields, writable=writable, defaults=defaults)
def serialize(self, obj: DjangoModel) -> NamedTuple:
pass
```

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@ -11,8 +11,7 @@ You can set a common prefix for all keys in this library using [CLICKHOUSE_STATS
## Gauges ## Gauges
* `<prefix>.sync.<model_name>.queue` * `<prefix>.sync.<model_name>.queue`
Number of elements in [intermediate storage](storages.md) queue waiting for import. Number of elements in [intermediate storage](storages.md) queue waiting for import.
<!--- TODO Add link ---> Queue should not be big. It depends on [sync_delay](synchronization.md#configuration) configured and time for syncing single batch.
Queue should not be big. It depends on [sync_delay]() configured and time for syncing single batch.
It is a good parameter to watch and alert on. It is a good parameter to watch and alert on.
## Timers ## Timers

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@ -76,7 +76,6 @@ from my_app.models import User
class ClickHouseUser(ClickHouseModel): class ClickHouseUser(ClickHouseModel):
django_model = User django_model = User
sync_delay = 5
id = fields.UInt32Field() id = fields.UInt32Field()
first_name = fields.StringField() first_name = fields.StringField()

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@ -1,3 +1,46 @@
# Sync performance # Sync performance
Every real life system may have its own performance problems.
They depend on:
* You ClickHouse servers configuration
* Number of ClickHouse instances in your cluster
* Your data formats
* Import speed
* Network
* etc
TODO I recommend to use [monitoring](monitoring.md) in order to understand where is the bottle neck and act accordingly.
This chapter gives a list of known problems which can slow down your import.
## ClickHouse tuning
Read this [doc](https://clickhouse.tech/docs/en/introduction/performance/#performance-when-inserting-data)
and tune it both for read and write.
## ClickHouse cluster
As ClickHouse is a [multimaster database](https://clickhouse.tech/docs/en/introduction/distinctive_features/#data-replication-and-data-integrity-support),
you can import and read from any node when you have a cluster.
In order to read and import to multiple nodes you can use [CHProxy](https://github.com/Vertamedia/chproxy)
or add multiple databases to [routing configuration](routing.md#clickhousemodel-routing-attributes).
## CollapsingMergeTree engine and previous versions
In order to reduce number of stored data in [intermediate storage](storages.md),
this library doesn't store old versions of data on update or delete.
Another point is that getting previous data versions from relational storages is a hard operation.
Engines like `CollapsingMergeTree` get old versions from ClickHouse:
1. Using `version_col` if it is set in engine's parameters.
This is a special field which stores incremental row versions and is filled by the library.
It should be of any unsigned integer type (depending on how many row versions you may have).
2. Using `FINAL` query modification.
This way is much more slow, but doesn't require additional column.
## Know your data
In common case library user uses python types to form ClickHouse data.
Library is responsible for converting this data into format ClickHouse expects to receive.
This leads to great number of convert operations when you import data in big batches.
In order to reduce this time, you can:
* Set `MyClickHouseModel.sync_formatted_tuples` to True
* Override `MyClickHouseModel.get_insert_batch(, import_objects: Iterable[DjangoModel])` method:
It should get `cls.get_tuple_class()` and yield (it is a [generator](https://wiki.python.org/moin/Generators))
so it generates tuples of string values, already prepared to insert into ClickHouse.
**Important note**: `ClickHouseModel.get_insert_batch(...)` can perform additional functionality depending on model [engine](models.md#engines).
Be careful.

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@ -1,3 +1,105 @@
# Synchronization # Synchronization
TODO ## Design motivation
Read [here](motivation.md#sync-over-intermediate-storage).
## Algorithm
<!--- ![General scheme](https://octodex.github.com/images/yaktocat.png) --->
1. [Celery beat](https://docs.celeryproject.org/en/latest/userguide/periodic-tasks.html) schedules `django_clickhouse.tasks.clickhouse_auto_sync` task every second or near.
2. [Celery workers](https://docs.celeryproject.org/en/latest/userguide/workers.html) execute `clickhouse_auto_sync`.
It searches for `ClickHouseModel` subclasses which need sync (if `Model.need_sync()` method returns `True`).
2. `django_clickhouse.tasks.sync_clickhouse_model` task is scheduled for each `ClickHouseModel` which needs sync.
3. `sync_clickhouse_model` saves sync start time in [storage](storages.md) and calls `ClickHouseModel.sync_batch_from_storage()` method.
4. `ClickHouseModel.sync_batch_from_storage()`:
* Gets [storage](storages.md) model works with using `ClickHouseModel.get_storage()` method
* Calls `Storage.pre_sync(import_key)` for model [storage](storages.md).
This may be used to prevent parallel execution with locks or some other operations.
* Gets a list of operations to sync from [storage](storages.md).
* Fetches objects from relational database calling `ClickHouseModel.get_sync_objects(operations)` method.
* Forms a batch of tuples to insert into ClickHouse using `ClickHouseModel.get_insert_batch(import_objects)` method.
* Inserts batch of tuples into ClickHouse using `ClickHouseModel.insert_batch(batch)` method.
* Calls `Storage.post_sync(import_key)` method to clean up storage after syncing batch.
This method also removes synced operations from storage.
* If some exception occurred during execution, `Storage.post_sybc_failed(import_key)` method is called.
Note, that process can be killed without exception, for instance by OOM killer.
And this method will not be called.
## Configuration
Sync configuration can be set globally using django settings.py parameters or redeclared for each `ClickHouseModel` class.
`ClickHouseModel` configuration is prior to settings configuration.
### Settings configuration
* [CLICKHOUSE_CELERY_QUEUE](configuration.md#clickhouse_celery_queue)
Defaults to: `'celery'`
A name of a queue, used by celery to plan library sync tasks.
* [CLICKHOUSE_SYNC_STORAGE](configuration.md#clickhouse_sync_storage)
Defaults to: `'django_clickhouse.storages.RedisStorage'`
An [intermediate storage](storages.md) class to use. Can be a string or class.
* [CLICKHOUSE_SYNC_BATCH_SIZE](configuration.md#clickhouse_sync_storage)
Defaults to: `10000`
Maximum number of operations, fetched by sync process from [intermediate storage](storages.md) per sync round.
* [CLICKHOUSE_SYNC_DELAY](configuration.md#clickhouse_sync_storage)
Defaults to: `5`
A delay in seconds between two sync rounds start.
### ClickHouseModel configuration
Each `ClickHouseModel` subclass can define sync arguments and methods:
* `django_model: django.db.models.Model`
Required.
Django model this ClickHouseModel class is synchronized with.
* `django_model_serializer: django.db.models.Model`
Defaults to: `django_clickhouse.serializers.Django2ClickHouseModelSerializer`
[Serializer class](models.md#serializers) to convert DjangoModel to ClickHouseModel.
* `sync_enabled: bool`
Defaults to: `False`.
Is sync for this model enabled?
* `sync_batch_size: int`
Defaults to: [CLICKHOUSE_SYNC_BATCH_SIZE](configuration.md#clickhouse_sync_storage)
Maximum number of operations, fetched by sync process from [storage](storages.md) per sync round.
* `sync_delay: float`
Defaults to: [CLICKHOUSE_SYNC_DELAY](configuration.md#clickhouse_sync_storage)
A delay in seconds between two sync rounds start.
* `sync_storage: Union[str, Storage]`
Defaults to: [CLICKHOUSE_SYNC_STORAGE](configuration.md#clickhouse_sync_storage)
An [intermediate storage](storages.md) class to use. Can be a string or class.
Example:
```python
from django_clickhouse.clickhouse_models import ClickHouseModel
from django_clickhouse.engines import ReplacingMergeTree
from infi.clickhouse_orm import fields
from my_app.models import User
class ClickHouseUser(ClickHouseModel):
django_model = User
sync_enabled = True
sync_delay = 5
sync_batch_size = 1000
id = fields.UInt32Field()
first_name = fields.StringField()
birthday = fields.DateField()
visits = fields.UInt32Field(default=0)
engine = ReplacingMergeTree('birthday', ('birthday',))
```
## Fail resistance
Fail resistance is based on several points:
1. [Storage](storages.md) should not loose data in any case. It's not this library goal to keep it stable.
2. Data is removed from [storage](storages.md) only if import succeeds. Otherwise import attempt is repeated.
3. It's recommended to use ReplacingMergeTree or CollapsingMergeTree [engines](models.md#engines)
instead of simple MergeTree, so it removes duplicates if batch is imported twice.
4. Each `ClickHouseModel` is synced in separate process.
If one model fails, it should not affect other models.

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@ -13,7 +13,7 @@ with open('requirements.txt') as f:
setup( setup(
name='django-clickhouse', name='django-clickhouse',
version='0.0.1', version='1.0.0',
packages=['django_clickhouse'], packages=['django_clickhouse'],
package_dir={'': 'src'}, package_dir={'': 'src'},
url='https://github.com/carrotquest/django-clickhouse', url='https://github.com/carrotquest/django-clickhouse',

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@ -1,3 +1,6 @@
import sys
from unittest import skipIf
from django.test import TestCase from django.test import TestCase
from django_clickhouse.compatibility import namedtuple from django_clickhouse.compatibility import namedtuple
@ -10,12 +13,16 @@ class NamedTupleTest(TestCase):
self.assertTupleEqual((1, 2, 4), tuple(TestTuple(1, 2, 4))) self.assertTupleEqual((1, 2, 4), tuple(TestTuple(1, 2, 4)))
self.assertTupleEqual((1, 2, 4), tuple(TestTuple(a=1, b=2, c=4))) self.assertTupleEqual((1, 2, 4), tuple(TestTuple(a=1, b=2, c=4)))
def test_exceptions(self): @skipIf(sys.version_info < (3, 7),
"On python < 3.7 this error is not raised, as not given defaults are filled by None")
def test_no_required_value(self):
TestTuple = namedtuple('TestTuple', ('a', 'b', 'c'), defaults=[3]) TestTuple = namedtuple('TestTuple', ('a', 'b', 'c'), defaults=[3])
# BUG On python < 3.7 this error is not raised, as not given defaults are filled by None with self.assertRaises(TypeError):
# with self.assertRaises(TypeError): TestTuple(b=1, c=4)
# TestTuple(b=1, c=4)
def test_duplicate_value(self):
TestTuple = namedtuple('TestTuple', ('a', 'b', 'c'), defaults=[3])
with self.assertRaises(TypeError): with self.assertRaises(TypeError):
TestTuple(1, 2, 3, c=4) TestTuple(1, 2, 3, c=4)