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Added usage examples
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examples/db_explorer/README.md
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examples/db_explorer/README.md
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# DB Explorer
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This is a simple Flask web application that connects to ClickHouse and displays the list of existing databases. Clicking on a database name drills down into it, showing its list of tables. Clicking on a table drills down further, showing details about the table and its columns.
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For each table or column, the application displays the compressed size on disk, the uncompressed size, and the ratio between them. Additionally, several pie charts are shown - top tables by size, top tables by rows, and top columns by size (in a table).
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The pie charts are generated using the `pygal` charting library.
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ORM concepts that are demonstrated by this example:
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- Creating ORM models from existing tables using `Database.get_model_for_table`
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- Queryset filtering
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- Queryset aggregation
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## Running the code
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Create a virtualenv and install the required libraries:
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```
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virtualenv -p python3.6 env
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source env/bin/activate
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pip install -r requirements.txt
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```
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Run the server and open http://127.0.0.1:5000/ in your browser:
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```
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python server.py
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```
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By default the server connects to ClickHouse running on http://localhost:8123/ without a username or password, but you can change this using command line arguments:
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```
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python server.py http://myclickhouse:8123/
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```
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or:
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```
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python server.py http://myclickhouse:8123/ admin secret123
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```
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@ -3,11 +3,18 @@ from pygal.style import RotateStyle
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from jinja2.filters import do_filesizeformat
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# Formatting functions
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number_formatter = lambda v: '{:,}'.format(v)
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bytes_formatter = lambda v: do_filesizeformat(v, True)
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def tables_piechart(db, by_field, value_formatter):
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'''
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Generate a pie chart of the top n tables in the database.
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`db` - the database instance
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`by_field` - the field name to sort by
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`value_formatter` - a function to use for formatting the numeric values
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'''
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Tables = db.get_model_for_table('tables', system_table=True)
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qs = Tables.objects_in(db).filter(database=db.db_name, is_temporary=False).exclude(engine='Buffer')
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tuples = [(getattr(table, by_field), table.name) for table in qs]
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def columns_piechart(db, tbl_name, by_field, value_formatter):
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'''
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Generate a pie chart of the top n columns in the table.
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`db` - the database instance
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`tbl_name` - the table name
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`by_field` - the field name to sort by
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`value_formatter` - a function to use for formatting the numeric values
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'''
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ColumnsTable = db.get_model_for_table('columns', system_table=True)
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qs = ColumnsTable.objects_in(db).filter(database=db.db_name, table=tbl_name)
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tuples = [(getattr(col, by_field), col.name) for col in qs]
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def _get_top_tuples(tuples, n=15):
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'''
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Given a list of tuples (value, name), this function sorts
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the list and returns only the top n results. All other tuples
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are aggregated to a single "others" tuple.
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'''
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non_zero_tuples = [t for t in tuples if t[0]]
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sorted_tuples = sorted(non_zero_tuples, reverse=True)
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if len(sorted_tuples) > n:
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@ -31,6 +50,11 @@ def _get_top_tuples(tuples, n=15):
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def _generate_piechart(tuples, value_formatter):
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'''
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Generates a pie chart.
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`tuples` - a list of (value, name) tuples to include in the chart
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`value_formatter` - a function to use for formatting the values
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'''
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style = RotateStyle('#9e6ffe', background='white', legend_font_family='Roboto', legend_font_size=18, tooltip_font_family='Roboto', tooltip_font_size=24)
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chart = pygal.Pie(style=style, margin=0, title=' ', value_formatter=value_formatter, truncate_legend=-1)
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for t in _get_top_tuples(tuples):
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@ -10,21 +10,34 @@ app = Flask(__name__)
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@app.route('/')
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def homepage_view():
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'''
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Root view that lists all databases.
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'''
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db = _get_db('system')
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# Get all databases in the system.databases table
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DatabasesTable = db.get_model_for_table('databases', system_table=True)
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databases = DatabasesTable.objects_in(db).exclude(name='system').order_by(F.lower(DatabasesTable.name))
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databases = DatabasesTable.objects_in(db).exclude(name='system')
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databases = databases.order_by(F.lower(DatabasesTable.name))
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# Generate the page
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return render_template('homepage.html', db=db, databases=databases)
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@app.route('/<db_name>/')
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def database_view(db_name):
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'''
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A view that displays information about a single database.
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'''
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db = _get_db(db_name)
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# Get all the tables in the database, by aggregating information from system.columns
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ColumnsTable = db.get_model_for_table('columns', system_table=True)
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tables = ColumnsTable.objects_in(db).filter(database=db_name).aggregate(ColumnsTable.table,
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tables = ColumnsTable.objects_in(db).filter(database=db_name).aggregate(
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ColumnsTable.table,
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compressed_size=F.sum(ColumnsTable.data_compressed_bytes),
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uncompressed_size=F.sum(ColumnsTable.data_uncompressed_bytes),
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ratio=F.sum(ColumnsTable.data_uncompressed_bytes) / F.sum(ColumnsTable.data_compressed_bytes)
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).order_by(F.lower(ColumnsTable.table))
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)
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tables = tables.order_by(F.lower(ColumnsTable.table))
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# Generate the page
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return render_template('database.html',
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db=db,
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tables=tables,
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@app.route('/<db_name>/<tbl_name>/')
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def table_view(db_name, tbl_name):
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'''
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A view that displays information about a single table.
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'''
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db = _get_db(db_name)
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# Get table information from system.tables
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TablesTable = db.get_model_for_table('tables', system_table=True)
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tbl_info = TablesTable.objects_in(db).filter(database=db_name, name=tbl_name)[0]
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# Get the SQL used for creating the table
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create_table_sql = db.raw('SHOW CREATE TABLE %s FORMAT TabSeparatedRaw' % tbl_name)
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# Get all columns in the table from system.columns
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ColumnsTable = db.get_model_for_table('columns', system_table=True)
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columns = ColumnsTable.objects_in(db).filter(database=db_name, table=tbl_name)
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# Generate the page
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return render_template('table.html',
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db=db,
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tbl_name=tbl_name,
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def _get_db(db_name):
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'''
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Returns a Database instance using connection information
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from the command line arguments (optional).
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'''
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db_url = sys.argv[1] if len(sys.argv) > 1 else 'http://localhost:8123/'
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username = sys.argv[2] if len(sys.argv) > 2 else None
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password = sys.argv[3] if len(sys.argv) > 3 else None
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