26 - Amazon Timestream¶

Creating resources¶

[10]:

import awswrangler as wr
import pandas as pd
from datetime import datetime

wr.timestream.create_database("sampleDB")
wr.timestream.create_table("sampleDB", "sampleTable", memory_retention_hours=1, magnetic_retention_days=1);

Write¶

[11]:

df = pd.DataFrame(
    {
        "time": [datetime.now(), datetime.now(), datetime.now()],
        "dim0": ["foo", "boo", "bar"],
        "dim1": [1, 2, 3],
        "measure": [1.0, 1.1, 1.2],
    }
)

rejected_records = wr.timestream.write(
    df=df,
    database="sampleDB",
    table="sampleTable",
    time_col="time",
    measure_col="measure",
    dimensions_cols=["dim0", "dim1"],
)

print(f"Number of rejected records: {len(rejected_records)}")

Number of rejected records: 0

Query¶

[12]:

wr.timestream.query(
    'SELECT time, measure_value::double, dim0, dim1 FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3'
)

[12]:

	time	measure_value::double	dim0	dim1
0	2020-12-08 19:15:32.468	1.0	foo	1
1	2020-12-08 19:15:32.468	1.2	bar	3
2	2020-12-08 19:15:32.468	1.1	boo	2

Deleting resources¶

[13]:

wr.timestream.delete_table("sampleDB", "sampleTable")
wr.timestream.delete_database("sampleDB")