This tutorial uses a dataset that contains second-by-second stock-trade data for
the top 100 most-traded symbols, in a hypertable named
also includes a separate table of company symbols and company names, in a
regular PostgreSQL table named
A service in Timescale is a cloud instance which contains your database.
Each service contains a single database, named
You can connect to a service from your local system using the
command-line utility. If you've used PostgreSQL before, you might already have
psql installed. If not, check out the installing psql section.
In the Timescale portal, click
Download the cheatsheetto download an SQL file that contains the login details for your new service. You can also copy the details directly from this page. When you have copied your password, click
I stored my password, go to service overviewat the bottom of the page.
When your service is ready to use, is shows a green
Runninglabel in the
Service Overview. You also receive an email confirming that your service is ready to use.
On your local system, at the command prompt, connect to the service using the
Service URLfrom the SQL file that you downloaded. When you are prompted, enter the password:psql -x "<SERVICE_URL>"Password for user tsdbadmin:
If your connection is successful, you'll see a message like this, followed by the
psqlprompt:psql (13.3, server 12.8 (Ubuntu 12.8-1.pgdg21.04+1))SSL connection (protocol: TLSv1.3, cipher: TLS_AES_256_GCM_SHA384, bits: 256, compression: off)Type "help" for help.tsdb=>
The dataset is updated on a nightly basis and contains data from the last four weeks, typically around 8 million rows of data. Stock trades are recorded in real-time Monday through Friday, typically during normal trading hours of the New York Stock Exchange (9:30 AM - 4:00 PM EST).
Hypertables are the core of Timescale. Hypertables enable Timescale to work efficiently with time-series data. Because Timescale is PostgreSQL, all the standard PostgreSQL tables, indexes, stored procedures and other objects can be created alongside your Timescale hypertables. This makes creating and working with Timescale tables similar to standard PostgreSQL.
Create a standard PostgreSQL table to store the real-time stock trade data using
CREATE TABLE:CREATE TABLE stocks_real_time (time TIMESTAMPTZ NOT NULL,symbol TEXT NOT NULL,price DOUBLE PRECISION NULL,day_volume INT NULL);
Convert the standard table into a hypertable partitioned on the
timecolumn using the
create_hypertable()function provided by Timescale. You must provide the name of the table and the column in that table that holds the timestamp data to use for partitioning:SELECT create_hypertable('stocks_real_time', by_range('time'));
Create an index to support efficient queries on the
timecolumns:CREATE INDEX ix_symbol_time ON stocks_real_time (symbol, time DESC);
When you create a hypertable, it is automatically partitioned on the time column you provide as the second parameter to
create_hypertable(). Also, Timescale automatically creates an index on the time column. However, you'll often filter your time-series data on other columns as well. Using indexes appropriately helps your queries perform better.
Because you often query the stock trade data by the company symbol, you should add an index for it. Include the time column because time-series data typically looks for data in a specific period of time.
When you have other relational data that enhances your time-series data, you can
create standard PostgreSQL tables just as you would normally. For this dataset,
there is one other table of data called
Add a table to store the company name and symbol for the stock trade data:CREATE TABLE company (symbol TEXT NOT NULL,name TEXT NOT NULL);
You now have two tables within your Timescale database. One hypertable named
stocks_real_time, and one normal PostgreSQL table named
This tutorial uses real-time stock trade data, also known as tick data, from Twelve Data.
To ingest data into the tables that you created, you need to download the dataset and copy the data to your database.
real_time_stock_data.zipfile. The file contains two
.csvfiles; one with company information, and one with real-time stock trades for the past month. Download:
In a new terminal window, run this command to unzip the
psqlprompt, use the
COPYcommand to transfer data into your Timescale instance. If the
.csvfiles aren't in your current directory, specify the file paths in these commands:\COPY stocks_real_time from './tutorial_sample_tick.csv' DELIMITER ',' CSV HEADER;\COPY company from './tutorial_sample_company.csv' DELIMITER ',' CSV HEADER;
Because there are millions of rows of data, the
COPYprocess could take a few minutes depending on your internet connection and local client resources.
The queries in this tutorial are suitable for visualizing in Grafana. If you want to visualize the results of your queries, connect your Grafana account to the energy consumption dataset.
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