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The Hyper-Fast Database that Truly Scales Simply get the best out of the SQL and NoSQL worlds. Whatever the complexity, volume and velocity of data, CrateDB allows you to perform complex queries in milliseconds, where other database technologies simply can’t. Get started for free Talk to an expert Talk to our engin...
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IoT & Sensor Data Geospatial Tracking Log Analysis /* Based on device data, this query returns the average * of the battery level for every hour for each device_id */ WITH avg_metrics AS ( SELECT device_id, DATE_BIN('1 hour'::INTERVAL, time, 0) AS period, AVG(battery_level) AS avg_...
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| 1480802400000 | demo000016 | iobeam | 36.06060606060606 | | 1480806000000 | demo000016 | iobeam | 35.45 | | 1480802400000 | demo000025 | iobeam | 12 | | 1480806000000 | demo000025 | iobeam | 16.475 | +---------------+------------+--------------+-----------...
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+------------+--------------------------+ Statement Result /* Based on the location of the International Space Station, * this query returns the 10 closest capital cities from * the last known position */ SELECT city as "City Name", country as "Country", DISTANCE(...
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Statement Result /* * Based on system event logs, this query calculates: * - a filter for specific messages using a full-text index * - the number of entries per minute * - the average scoring ratio for each matched row */ SELECT DATE_TRUNC('minute', receivedat) AS event_time, COUNT(*) AS ...
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| 1620219720000 | 13 | 1.5637413492569556 | +---------------+---------+--------------------+ Statement Result Upcoming Events October 10, 2023 - October 11, 2023 14:00 - 16:00 CET Webinar CrateDB Workshop 2nd edition CrateDB Workshop is a hands-on learning experience for novel and ex...
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Feedback   Suggest improvement   Edit page   View page source latest CrateDB Python Client¶ Table of contents Introduction Documentation Project information Introduction¶ The Python client library for CrateDB implements the Python Database API Specification v2.0 (PEP 24...
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cursor.close() Connect to CrateDB Cloud. # Connect using DB API. from crate import client connection = client.connect( servers="https://example.aks1.westeurope.azure.cratedb.net:4200", username="admin", password="<PASSWORD>") SQLAlchemy¶ The CrateDB dialect for SQLAlchemy offers convenient ORM access and su...
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engine = sa.create_engine(dburi, echo=True) with engine.connect() as connection: df = pd.read_sql(sql=sa.text(query), con=connection) df.info() print(df) Data types¶ The DB API driver and the SQLAlchemy dialect support CrateDB’s data types to different degrees. For more information, please consult the Data ...
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License¶ The project is licensed under the terms of the Apache 2.0 license, like CrateDB itself, see LICENSE.
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Feedback   Suggest improvement   Edit page   View page source latest Other connectivity options for Python¶ Introduction¶ Using the PostgreSQL wire protocol interface of CrateDB, there are a few other connectivity options for Python. This section enumerates the verified...
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Feedback   Suggest improvement   Edit page   View page source latest CrateDB Python Client¶ Table of contents Introduction Documentation Project information Introduction¶ The Python client library for CrateDB implements the Python Database API Specification v2.0 (PEP 24...
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cursor.close() Connect to CrateDB Cloud. # Connect using DB API. from crate import client connection = client.connect( servers="https://example.aks1.westeurope.azure.cratedb.net:4200", username="admin", password="<PASSWORD>") SQLAlchemy¶ The CrateDB dialect for SQLAlchemy offers convenient ORM access and su...
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engine = sa.create_engine(dburi, echo=True) with engine.connect() as connection: df = pd.read_sql(sql=sa.text(query), con=connection) df.info() print(df) Data types¶ The DB API driver and the SQLAlchemy dialect support CrateDB’s data types to different degrees. For more information, please consult the Data ...
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License¶ The project is licensed under the terms of the Apache 2.0 license, like CrateDB itself, see LICENSE.
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Feedback   Suggest improvement   Edit page   View page source latest CrateDB Python Client – all pages¶ Table of contents Getting started Install Interactive use Set up as a dependency Next steps Connect to CrateDB Connect to a single node Connect to multiple nodes Conn...
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy support¶ Table of contents Introduction Connecting Database URLs Getting a connection Tables Table definition Extension types Querying Aggregate functions Fulltext search Introduction¶ SQLAl...
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can add the query parameter ?ssl=true to the database URI. Example database URIs: crate://localhost:4200 crate://crate-1.vm.example.com:4200 crate://username:password@crate-2.vm.example.com:4200/?ssl=true crate://198.51.100.1:4200 Tip If <HOST> is blank (i.e. the database URI is just crate://), then localhost:4200 will...
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>>> engine = sa.create_engine( ... 'crate://', ... connect_args={ ... 'servers': ['198.51.100.1:4200', '198.51.100.2:4200'], ... 'ca_cert': '<PATH_TO_CA_CERT>', ... } ... ) In order to disable SSL verification, use verify_ssl_cert = False, like: >>> engine = sa.create_engine( ... 'crate:...
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>>> class Character(Base): ... ... __tablename__ = 'characters' ... __table_args__ = { ... 'crate_number_of_shards': 3 ... } ... ... id = sa.Column(sa.String, primary_key=True, default=gen_key) ... name = sa.Column(sa.String, crate_index=False) ... name_normalized = sa.Column(sa.String, ...
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the mapping (so SQLAlchemy doesn’t try to update them as if they were columns) Disable the columnstore of the even_more_details column using crate_columnstore=False Add a created_at column whose default value is set by CrateDB’s now() function. Tip This example table is used throughout the rest of this document. See al...
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... ts = sa.Column(sa.DateTime, server_default=sa.func.current_timestamp()) ... level = sa.Column(sa.String) ... message = sa.Column(sa.String) >>> log = Log(level="info", message="Hello World") >>> session.add(log) >>> session.commit() >>> log.id ... Auto-generated primary key¶ CrateDB 4.5.0 added the gen_...
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insert two records: >>> # use the crate engine from earlier examples >>> Session = sessionmaker(bind=crate) >>> session = Session() >>> arthur = Character(name='Arthur Dent') >>> arthur.details = {} >>> arthur.details['gender'] = 'male' >>> arthur.details['species'] = 'human' >>> session.add(arthur) >>> trillian = Char...
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>>> session.commit() The resulting object will look like this: >>> arthur.more_details [{'foo': 1, 'bar': 10}, {'foo': 2}, {'foo': 3}] Caution Behind the scenes, if you update an ObjectArray, and commit that change, the UPDATE statement sent to CrateDB will include all of the ObjectArray data. Geopoint and Geoshape¶ Th...
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... (139.584, 35.619), ... (139.806, 35.515), ... ] ... ] ... ) You can then set the values of the Geopoint and Geoshape columns: >>> tokyo = City(name="Tokyo", coordinate=point, area=area) >>> session.add(tokyo) >>> session.commit() Querying¶ When the commit method is called, two IN...
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>>> from sqlalchemy.sql import operators >>> query = session.query(Character.name) >>> query.filter(Character.more_details['foo'].any(1, operator=operators.eq)).all() [(u'Arthur Dent',)] Here, we’re using SQLAlchemy’s any method along with Python’s operator.eq() function, in order to match the value 1 against the key f...
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... .group_by(Character.name) \ ... .order_by(sa.desc(sa.func.count(Character.id))) \ ... .order_by(Character.name).all() [(1, u'Arthur Dent'), (1, u'Tricia McMillan')] Fulltext search¶ Matching¶ Fulltext Search in CrateDB is done with the MATCH Predicate. The CrateDB SQLAlchemy dialect provides a match fun...
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match_type (optional) The Match Types. Determine how the term is applied and the _score gets calculated. See also score usage. Here’s an example: match({Character.name_ft: 0.5, Character.details['name']['first']: 0.8, Character.details['name']['last']: 0.2}, 'Trillian', match_type='phrase') op...
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index. And we’re selecting the name column of the character by using the table definition But notice that we select the associated score by passing in the virtual column name as a string (_score) instead of using a defined column on the Character class.
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Feedback   Suggest improvement   Edit page   View page source latest Data types¶ The Database API client and the SQLAlchemy dialect use different Python data types. Consult the corresponding section for further information. Table of contents Database API client SQLAlche...
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CrateDB SQLAlchemy boolean Boolean byte SmallInteger short SmallInteger integer Integer long NUMERIC float Float double DECIMAL timestamp TIMESTAMP string String array ARRAY object ObjectType (extension type) array(object) ObjectArray (extension type) geo_point Geopoint and Geoshape (extension type) geo_shape Geopoint ...
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Feedback   Suggest improvement   Edit page   View page source latest Getting started¶ Learn how to install and get started with the Python client library for CrateDB. Table of contents Install Interactive use Set up as a dependency Next steps Install¶ The CrateDB Python...
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Feedback   Suggest improvement   Edit page   View page source latest Blobs¶ The CrateDB Python client library provides full access to the powerful blob storage capabilities of your CrateDB cluster. Table of contents Get a blob container Working with the blob container U...
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The io.StringIO class is not suitable, as it produces Unicode strings when read. But you can easily encode a Unicode string and feed it to a io.BytesIO object. Here’s a trivial example: >>> import io >>> bytestream = "An example sentence.".encode("utf8") >>> file = io.BytesIO(bytestream) This file can then be uploaded ...
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And upload it: >>> blob_container.put(another_file, digest) True The put method returns True, indicating that the object has been written to the blob container. Retrieve blobs¶ To retrieve a blob, you need to know its digest. Let’s use the digest variable we created before to check whether that object exists with the e...
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Feedback   Suggest improvement   Edit page   View page source latest Query CrateDB¶ Note This page documents the CrateDB client, implementing the Python Database API Specification v2.0 (PEP 249). For help using the SQLAlchemy dialect, consult the SQLAlchemy dialect docu...
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>>> cursor.executemany( ... "INSERT INTO locations (name, date, kind, position) VALUES (?, ?, ?, ?)", ... [('Cloverleaf', '2007-03-11', 'Quasar', 7), ... ('Old Faithful', '2007-03-11', 'Quasar', 7)]) [{'rowcount': 1}, {'rowcount': 1}] The executemany() method returns a result dictionary for every tuple. Th...
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returns the specified number of result rows: >>> cursor.execute("SELECT name FROM locations order by name") >>> result = cursor.fetchmany(2) >>> pprint(result) [['Aldebaran'], ['Algol']] If a number is not given as an argument, fetch_many() will return a result list with one result row: >>> cursor.fetchmany() [['Allosi...
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('description', None, None, None, None, None, None), ... ('nullable_datetime', None, None, None, None, None, None), ('position', None, None, None, None, None, None)) You can turn this into something more manageable with List Comprehensions: >>> [column[0] for column in cursor.description] ['date', 'datetime_tz', 'dat...
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>>> from crate.client.converter import Converter, DataType >>> converter = Converter() >>> converter.set(DataType.BOOLEAN, lambda value: value is True and "yes" or "no") >>> cursor = connection.cursor(converter=converter) >>> cursor.execute("SELECT flag FROM locations ORDER BY name") >>> cursor.fetchone() ['no'] TIMEST...
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>>> import pytz >>> cursor.time_zone = pytz.timezone("Australia/Sydney") >>> cursor.execute("SELECT datetime_tz FROM locations ORDER BY name") >>> cursor.fetchone() ['foo', datetime.datetime(2022, 7, 19, 4, 10, 36, 758000, tzinfo=<DstTzInfo 'Australia/Sydney' AEST+10:00:00 STD>)] >>> try: ... import zoneinfo ... ex...
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Feedback   Suggest improvement   Edit page   View page source latest Index
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Feedback   Suggest improvement latest Search From here you can search these documents. Enter your search words into the box below and click "search". Note that the search function will automatically search for all of the words. Pages containing fewer words won't appear in the result li...
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Feedback   Suggest improvement   Edit page   View page source latest Connect to CrateDB¶ Note This page documents the CrateDB client, implementing the Python Database API Specification v2.0 (PEP 249). For help using the SQLAlchemy dialect, consult the SQLAlchemy dialect...
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i.e. http://localhost:4200/. If you’re just getting started with CrateDB, the first time you connect, you can probably omit this argument. Connect to multiple nodes¶ To connect to one of multiple nodes, pass a list of database URLs to the connect() function, like so: >>> connection = client.connect(["<NODE_1_URL>", "<N...
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>>> connection = client.connect(..., verify_ssl_cert=False) Client verification¶ The client also supports client verification via client certificates. Here’s how you might do that: >>> connection = client.connect(..., cert_file="<CERT_FILE>", key_file="<KEY_FILE>") Here, replace <CERT_FILE> with the path to the client ...
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>>> connection = client.connect(..., backoff_factor=0.1) If backoff_factor is set to 0.1, then the delay between retries will be 0.0, 0.1, 0.2, 0.4 etc. The maximum backoff factor cannot exceed 120 seconds and by default its value is 0. Socket Options¶ Creating connections uses urllib3 default socket options but additi...
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Here, replace <USERNAME> and <PASSWORD> with the appropriate username and password. Tip If you have not configured a custom database user, you probably want to authenticate as the CrateDB superuser, which is crate. The superuser does not have a password, so you can omit the password argument. Schema selection¶ You can ...
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Feedback   Suggest improvement   Edit page   View page source latest Database client¶ crate.client.connect is the primary method to connect to CrateDB using Python. This section of the documentation outlines different methods to connect to the database cluster, as well ...
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>>> connection = client.connect([crate_host], error_trace=True) >>> connection.close() It’s possible to define a default timeout value in seconds for all servers using the optional parameter timeout: >>> connection = client.connect([crate_host, invalid_host], timeout=5) >>> connection.close() Authentication¶ Users that...
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... schema='custom_schema') >>> connection.close() Inserting Data¶ Use user “crate” for rest of the tests: >>> connection = client.connect([crate_host]) Before executing any statement, a cursor has to be opened to perform database operations: >>> cursor = connection.cursor() >>> cursor.execu...
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>>> timestamp_date = "2023-06-26" >>> datetime_aware = dt.datetime.fromisoformat("2023-06-26T09:24:00.123+02:00") >>> datetime_naive = dt.datetime.fromisoformat("2023-06-26T09:24:00.123") >>> datetime_date = dt.date.fromisoformat("2023-06-26") >>> cursor.execute("UPDATE locations SET date=? WHERE name='Cloverleaf'", (t...
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>>> pprint(result) [['Aldebaran'], ['Algol']] If a size is not given, the cursor’s arraysize, which defaults to ‘1’, determines the number of rows to be fetched: >>> cursor.fetchmany() [['Allosimanius Syneca']] It’s also possible to change the cursors arraysize to an other value: >>> cursor.arraysize = 3 >>> cursor.fet...
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'Max Quordlepleen claims that the only thing left after the end of the ' 'Universe will be the sweets trolley and a fine selection of Aldebaran ' 'liqueurs.', None] >>> result = cursor.description >>> pprint(result) (('name', None, None, None, None, None, None), ('date', None, None, None, None, None, None), ('date...
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>>> cursor.execute("SELECT * FROM locations") Traceback (most recent call last): ... crate.client.exceptions.ProgrammingError: Connection closed >>> cursor = connection.cursor() Traceback (most recent call last): ... crate.client.exceptions.ProgrammingError: Connection closed
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Feedback   Suggest improvement   Edit page   View page source latest By example¶ This part of the documentation enumerates different kinds of examples how to use the CrateDB Python client. DB API, HTTP, and BLOB interfaces¶ The examples in this section are all about Cra...
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Feedback   Suggest improvement   Edit page   View page source latest HTTPS connection support¶ This documentation section outlines different options to connect to CrateDB using SSL/TLS. Table of Contents Introduction With certificate verification Without certificate ver...
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>>> client.server_infos(crate_host) Traceback (most recent call last): ... crate.client.exceptions.ConnectionError: Server not available, ...certificate verify failed... Without certificate verification¶ When turning off certificate verification, calling the server will succeed, even when not providing a valid CA certi...
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>>> client.server_infos(crate_host) Traceback (most recent call last): ... crate.client.exceptions.ConnectionError: Server not available, exception: HTTPSConnectionPool... Relaxing minimum SSL version¶ urrlib3 v2 dropped support for TLS 1.0 and TLS 1.1 by default, see Modern security by default - HTTPS requires TLS 1.2...
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Feedback   Suggest improvement   Edit page   View page source latest HTTP client¶ Table of Contents Introduction Server configuration SQL Statements Blobs Error Handling Introduction¶ The CrateDB Python driver package offers an HTTP client API object. >>> from crate.cli...
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>>> result = http_client.sql('select name from locations') >>> http_client._active_servers ['http://127.0.0.1:44209'] Inactive servers will be re-added after a given time interval. To validate this, set the interval very short and sleep for that interval: >>> http_client.retry_interval = 1 >>> import time; time.sleep(1...
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['Galactic Sector QQ7 Active J Gamma'], ['Galaxy'], ['North West Ripple'], ['Outer Eastern Rim']]} Blobs¶ Check if a blob exists: >>> http_client.blob_exists('myfiles', '040f06fd774092478d450774f5ba30c5da78acc8') False Trying to get a non-existing blob throws an exception: >>> http_client....
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True Blobs are returned as generators, generating a chunk on each call: >>> g = http_client.blob_get('myfiles', '040f06fd774092478d450774f5ba30c5da78acc8') >>> print(next(g)) content The chunk_size can be set explicitly on get: >>> g = http_client.blob_get( ... 'myfiles', '040f06fd774092478d450774f5ba30c5da78acc8',...
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... CREATE FUNCTION fib(LONG) RETURNS LONG ... LANGUAGE JAVASCRIPT AS ' ... var fib = function fib(n) { return n < 2 ? n : fib(n-1) + fib(n-2); } ... ' ... ''') {...} >>> http_client.close() It’s possible to define a HTTP timeout in seconds on client instantiation, so an exception is raised when the timeout is reache...
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Feedback   Suggest improvement   Edit page   View page source latest The Connection object¶ This documentation section outlines different attributes, methods, and behaviors of the crate.client.connection.Connection object. The examples use an instance of ClientMocked in...
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Feedback   Suggest improvement   Edit page   View page source latest Blob container API¶ The connection object provides a convenience API for easy access to blob tables. Get blob container handle¶ Create a connection: >>> from crate.client import connect >>> client = co...
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>>> blob_stream = container.get(string_blob) >>> blob_stream <generator ...> >>> data = next(blob_stream) >>> data == string_data True Delete blobs¶ Blobs can be deleted using its hash: >>> container.delete(string_blob) True >>> container.exists(string_blob) False Trying to delete a not existing blob: >>> container.del...
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Feedback   Suggest improvement   Edit page   View page source latest The Cursor object¶ This documentation section outlines different attributes, methods, and behaviors of the crate.client.cursor.Cursor object. The example code uses ClientMocked and set_next_response fo...
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>>> cursor.execute('') >>> cursor.fetchone() ['North West Ripple', 1] Each call to fetchone() increments the cursor and returns the next row: >>> cursor.fetchone() ['Arkintoofle Minor', 3] One more iteration: >>> cursor.next() ['Alpha Centauri', 3] The iteration is stopped after the last row is returned. A further call...
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[['Alpha Centauri', 3]] fetchall()¶ fetchall() fetches all (remaining) rows of a query result: >>> cursor.execute('') >>> cursor.fetchall() [['North West Ripple', 1], ['Arkintoofle Minor', 3], ['Alpha Centauri', 3]] Since all data was fetched ‘None’ is returned by fetchone(): >>> cursor.fetchone() And each other call r...
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The rowcount property specifies the number of rows that the last execute() produced: >>> cursor.execute('') >>> cursor.rowcount 3 The attribute is -1, in case the cursor has been closed: >>> cursor.close() >>> cursor.rowcount -1 If the last response does not contain the rowcount attribute, -1 is returned: >>> cursor = ...
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of parameters: >>> cursor = connection.cursor() >>> cursor.executemany('', (1,2,3)) [{'rowcount': 3}, {'rowcount': 2}] >>> cursor.rowcount 5 >>> cursor.duration 123 executemany() is not intended to be used with statements returning result sets. The result will always be empty: >>> cursor.fetchall() [] For completeness’...
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Python data type conversion¶ The cursor object can optionally convert database types to native Python data types. Currently, this is implemented for the CrateDB data types IP and TIMESTAMP on behalf of the DefaultTypeConverter. >>> cursor = connection.cursor(converter=DefaultTypeConverter()) >>> connection.client.set_n...
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... "cols":[ "value" ], ... "rowcount":1, ... "duration":123 ... }) >>> cursor.execute('') >>> cursor.fetchone() [6] TIMESTAMP conversion with time zone¶ Based on the data type converter functionality, the driver offers a convenient interface to make it return timezone-aware datetime objects, using the desi...
https://cratedb.com/docs/python/en/latest/by-example/cursor.html
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>>> cursor.time_zone = datetime.timezone.utc >>> cursor.execute('') >>> cursor.fetchone() ['foo', datetime.datetime(2022, 7, 18, 18, 10, 36, 758000, tzinfo=datetime.timezone.utc)] >>> import pytz >>> cursor.time_zone = pytz.timezone("Australia/Sydney") >>> cursor.execute('') >>> cursor.fetchone() ['foo', datetime.datet...
https://cratedb.com/docs/python/en/latest/by-example/cursor.html
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy: DataFrame operations¶ Table of Contents About Introduction pandas Dask Compatibility notes Efficient INSERT operations with pandas Efficient INSERT operations with Dask About¶ This section ...
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and NumPy. A Dask DataFrame is a large parallel DataFrame composed of many smaller pandas DataFrames, split along the index. These pandas DataFrames may live on disk for larger-than-memory computing on a single machine, or on many different machines in a cluster. One Dask DataFrame operation triggers many operations on...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/dataframe.html
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... method=insert_bulk, ... ) Tip You will observe that the optimal chunk size highly depends on the shape of your data, specifically the width of each record, i.e. the number of columns and their individual sizes, which will in the end determine the total size of each batch/chunk. A few details should be taken int...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/dataframe.html
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then see if performance improves when you increase or decrease that figure. People are reporting that 10_000-20_000 is their optimal setting, but if you process, for example, just three “small” columns, you may also experiment with leveling up to 200_000, because the chunksize should not be too small. If it is too smal...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/dataframe.html
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>>> CHUNK_SIZE = 25 ... >>> # Create a Dask DataFrame. >>> df = makeTimeDataFrame(nper=INSERT_RECORDS, freq="S") >>> ddf = dd.from_pandas(df, npartitions=NPARTITIONS) ... >>> # Insert content of DataFrame using multiple workers on a >>> # compute cluster, transferred using batches of records. >>> ddf.to_sql( ... na...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/dataframe.html
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Adjusting this value in both directions is perfectly fine: If you observe that you are overloading the machine, maybe because there are workloads scheduled other than the one you are running, try to reduce the value. If fragments/steps of your implementation involve waiting for network or disk I/O, you may want to incr...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/dataframe.html
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy: Advanced querying¶ This section of the documentation demonstrates running queries using a fulltext index with an analyzer, queries using counting and aggregations, and support for the INSER...
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) We have to create this table using SQL because it is currently not possible to create INDEX fields using SQLAlchemy’s Declarative Mapping. However, we can define the table to use all other operations: >>> def gen_key(): ... return str(uuid4()) >>> class Character(Base): ... __tablename__ = 'characters' ... ...
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Fulltext search in CrateDB is performed using MATCH Predicate. The CrateDB SQLAlchemy dialect comes with a match function, which can be used to search on one or multiple fields. >>> from crate.client.sqlalchemy.predicates import match >>> session.query(Character.name) \ ... .filter(match(Character.name_ft, 'Arthur'...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/advanced-querying.html
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function. >>> session.query(Character.name) \ ... .filter( ... match(Character.name_ft, 'Arth', ... match_type='phrase', ... options={'fuzziness': 3}) ... ) \ ... .all() [('Arthur Dent',)] It is not possible to specify options without the match_type argument: >>> sess...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/advanced-querying.html
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functionality is supported by the CrateDB client library. Here is an example that uses insert().from_select(). First, let’s define and create the tables: >>> from sqlalchemy import select, insert >>> class Todos(Base): ... __tablename__ = 'todos' ... __table_args__ = { ... 'crate_number_of_replicas': '0...
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>>> _ = connection.execute(sa.text("REFRESH TABLE archived_tasks")) >>> pprint([str(r) for r in session.execute(sa.text("SELECT content FROM archived_tasks"))]) ["('Write Tests',)"] INSERT...RETURNING¶ The RETURNING clause can be used to retrieve the result rows of an INSERT operation. It may be specified using the Ins...
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Insert a user and get the user id: >>> from sqlalchemy import insert, update >>> stmt = insert(User).values(username='Arthur Dent', email='arthur_dent@crate.io').returning(User.id, User.username, User.email) >>> result = session.execute(stmt) >>> session.commit() >>> uid = [r[0] for r in result][0] Now let’s update the...
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy: Getting started¶ This section of the documentation shows how to connect to CrateDB using its SQLAlchemy dialect, and how to run basic DDL statements based on an SQLAlchemy ORM schema defini...
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>>> sa.create_engine('crate://otherserver:4200') Engine(crate://otherserver:4200) Multiple Hosts¶ Because CrateDB is a clustered database running on multiple servers, it is recommended to connect to all of them. This enables the DB-API layer to use round-robin to distribute the load and skip a server if it becomes unav...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/getting-started.html
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42.42 or use the timeout URL parameter within the database connection URL. >>> timeout_engine = sa.create_engine('crate://localhost/?timeout=42.42') >>> timeout_engine.raw_connection().driver_connection.client._pool_kw["timeout"] 42.42 Pool Size¶ In order to configure the database connection pool size, use the pool_siz...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/getting-started.html
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>>> engine.dialect.has_table(connection, table_name='departments') False In order to create all missing tables, the create_all method can be used: >>> Base.metadata.create_all(bind=engine) With that, the table has been created: >>> engine.dialect.has_table(connection, table_name='departments') True Let’s also verify th...
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy: Database schema inspection and reflection¶ This section shows you how to inspect the schema of a database using CrateDB’s SQLAlchemy integration. Introduction¶ The CrateDB SQLAlchemy integr...
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>>> inspector.default_schema_name 'doc' Schema-supported reflection¶ A Table object can load its own schema information from the corresponding table in the database. This process is called reflection, see Reflecting Database Objects. In the most simple case you need only specify the table name, a MetaData object, and t...
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy: Create, retrieve, update, and delete¶ This section of the documentation shows how to query, insert, update and delete records using CrateDB’s SQLAlchemy integration, it includes common scen...
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... details = sa.Column(ObjectArray) Create an SQLAlchemy Session: >>> session = sessionmaker(bind=engine)() Create¶ Insert a new location: >>> location = Location() >>> location.name = 'Earth' >>> location.kind = 'Planet' >>> location.flag = True >>> session.add(location) >>> session.flush() Refresh “locations” ta...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/crud.html
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>>> [l.name for l in locations if l is not None] ['Algol', 'Allosimanius Syneca'] With filter: >>> location = session.query(Location).filter_by(name='Algol').one() >>> location.name 'Algol' Order by: >>> locations = session.query(Location).filter(Location.name is not None).order_by(sa.desc(Location.name)) >>> locations...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/crud.html
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>>> _ = connection.execute(text("REFRESH TABLE locations")) Update multiple records using SQL: >>> with engine.begin() as conn: ... result = conn.execute(text("update locations set flag=true where kind='Update'")) ... result.rowcount 10 Update all records using SQL, and check that the number of documents affect...
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/crud.html
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>>> session.delete(location) >>> session.commit() >>> session.flush() >>> _ = connection.execute(text("REFRESH TABLE locations")) >>> session.query(Location).count() 23
https://cratedb.com/docs/python/en/latest/by-example/sqlalchemy/crud.html
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Feedback   Suggest improvement   Edit page   View page source latest SQLAlchemy: Working with special CrateDB types¶ This section of the documentation shows how to work with special data types from the CrateDB SQLAlchemy dialect. Currently, these are: Container types Ob...
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