If you have data stored in an external .csv
file, you can import it into
Timescale.
Note
You can use the Timescale parallel copy tool to speed up data copying. The tool parallelizes migration by using several workers to run multiple COPY
operations concurrently. It also offers options to improve the copying experience. If you prefer not to use timescaledb-parallel-copy
, you can also use regular PostgreSQL COPY
. This section provides instructions for both methods.
Before you start, make sure you have:
- Signed up for your free Timescale account.
- Checked that your source data uses a schema that matches the database you want to import it into.
- Ensured that the
time
column in the source data uses theTIMESTAMPTZ
data type.
Import data from a csv
.
Connect to your database and create a new empty table. Use a schema that matches the data in your
.csv
file. In this example, the.csv
file contains the columnsts
,location
, andtemperature
.CREATE TABLE <TABLE_NAME> (ts TIMESTAMPTZ NOT NULL,location TEXT NOT NULL,temperature DOUBLE PRECISION NULL);Convert the empty table to a hypertable using the
create_hypertable
function. Replacets
with the name of the column storing time values in your table.SELECT create_hypertable('<TABLE_NAME>', by_range('ts'))At the command line, insert data into the hypertable from your
csv
. Usetimescaledb-parallel-copy
to speed up migration. Adjust the number of workers as desired. Alternatively see the next step.timescaledb-parallel-copy --db-name <DATABASE_NAME> --table <TABLE_NAME> \--file <FILENAME>.csv --workers 4 --copy-options "CSV"OptionalIf you don't want to use
timescaledb-parallel-copy
, insert data into the hypertable by using PostgreSQL's nativeCOPY
command. At the command line, run:psql -d <DATABASE_NAME> -c "\COPY <TABLE_NAME> FROM <FILENAME>.csv CSV"
Note
Don't set the number of workers for timescaledb-parallel-copy
higher than the number of available CPU cores. Above that, workers compete with each other for resources and reduce the performance improvements.
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