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# Appending to and overwriting a Delta Lake table | ||
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This section explains how to append to an exising Delta table and how to overwrite a Delta table. | ||
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## Delta Lake append transactions | ||
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Suppose you have a Delta table with the following contents: | ||
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``` | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 1 | a | | ||
| 2 | b | | ||
| 3 | c | | ||
+-------+----------+ | ||
``` | ||
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Append two additional rows of data to the table: | ||
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```python | ||
from deltalake import write_deltalake, DeltaTable | ||
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df = pd.DataFrame({"num": [8, 9], "letter": ["dd", "ee"]}) | ||
write_deltalake("tmp/some-table", df, mode="append") | ||
``` | ||
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Here are the updated contents of the Delta table: | ||
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``` | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 1 | a | | ||
| 2 | b | | ||
| 3 | c | | ||
| 8 | dd | | ||
| 9 | ee | | ||
+-------+----------+ | ||
``` | ||
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Now let's see how to perform an overwrite transaction. | ||
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## Delta Lake overwrite transactions | ||
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Now let's see how to overwrite the exisitng Delta table. | ||
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```python | ||
df = pd.DataFrame({"num": [11, 22], "letter": ["aa", "bb"]}) | ||
write_deltalake("tmp/some-table", df, mode="overwrite") | ||
``` | ||
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Here are the contents of the Delta table after the overwrite operation: | ||
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``` | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 11 | aa | | ||
| 22 | bb | | ||
+-------+----------+ | ||
``` | ||
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Overwriting just performs a logical delete. It doesn't physically remove the previous data from storage. Time travel back to the previous version to confirm that the old version of the table is still accessable. | ||
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``` | ||
dt = DeltaTable("tmp/some-table", version=1) | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 1 | a | | ||
| 2 | b | | ||
| 3 | c | | ||
| 8 | dd | | ||
| 9 | ee | | ||
+-------+----------+ | ||
``` |
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# Creating a Delta Lake Table | ||
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This section explains how to create a Delta Lake table. | ||
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You can easily write a DataFrame to a Delta table. | ||
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```python | ||
from deltalake import write_deltalake | ||
import pandas as pd | ||
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df = pd.DataFrame({"num": [1, 2, 3], "letter": ["a", "b", "c"]}) | ||
write_deltalake("tmp/some-table", df) | ||
``` | ||
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Here are the contents of the Delta table in storage: | ||
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``` | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 1 | a | | ||
| 2 | b | | ||
| 3 | c | | ||
+-------+----------+ | ||
``` |
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# Deleting rows from a Delta Lake table | ||
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This section explains how to delete rows from a Delta Lake table. | ||
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Suppose you have the following Delta table with four rows: | ||
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``` | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 1 | a | | ||
| 2 | b | | ||
| 3 | c | | ||
| 4 | d | | ||
+-------+----------+ | ||
``` | ||
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Here's how to delete all the rows where the `num` is greater than 2: | ||
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```python | ||
dt = DeltaTable("tmp/my-table") | ||
dt.delete("num > 2") | ||
``` | ||
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Here are the contents of the Delta table after the delete operation has been performed: | ||
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``` | ||
+-------+----------+ | ||
| num | letter | | ||
|-------+----------| | ||
| 1 | a | | ||
| 2 | b | | ||
+-------+----------+ | ||
``` |
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# Delta Lake Z Order | ||
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This section explains how to Z Order a Delta table. | ||
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Z Ordering colocates similar data in the same files, which allows for better file skipping and faster queries. | ||
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Suppose you have a table with `first_name`, `age`, and `country` columns. | ||
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If you Z Order the data by the `country` column, then individuals from the same country will be stored in the same files. When you subquently query the data for individuals from a given country, it will execute faster because more data can be skipped. | ||
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Here's how to Z Order a Delta table: | ||
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```python | ||
dt = DeltaTable("tmp") | ||
dt.optimize.z_order([country]) | ||
``` |
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