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docs: document inlining of small data in read_* APIs (#670)
* docs: document inlining of small data in `read_*` APIs * mention that threshold is in memory size * non-bigquery instead of non-"bigquery"
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bigframes/session/__init__.py

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@@ -874,6 +874,11 @@ def read_pandas(
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The pandas DataFrame will be persisted as a temporary BigQuery table, which can be
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automatically recycled after the Session is closed.
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.. note::
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Data is inlined in the query SQL if it is small enough (roughly 5MB
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or less in memory). Larger size data is loaded to a BigQuery table
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instead.
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**Examples:**
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>>> import bigframes.pandas as bpd

third_party/bigframes_vendored/pandas/io/parquet.py

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@@ -19,6 +19,11 @@ def read_parquet(
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Instead, set a serialized index column as the index and sort by
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that in the resulting DataFrame.
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.. note::
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For non-"bigquery" engine, data is inlined in the query SQL if it is
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small enough (roughly 5MB or less in memory). Larger size data is
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loaded to a BigQuery table instead.
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**Examples:**
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>>> import bigframes.pandas as bpd

third_party/bigframes_vendored/pandas/io/parsers/readers.py

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@@ -62,6 +62,11 @@ def read_csv(
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file. Instead, set a serialized index column as the index and sort by
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that in the resulting DataFrame.
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.. note::
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For non-bigquery engine, data is inlined in the query SQL if it is
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small enough (roughly 5MB or less in memory). Larger size data is
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loaded to a BigQuery table instead.
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**Examples:**
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>>> import bigframes.pandas as bpd
@@ -167,6 +172,11 @@ def read_json(
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file. Instead, set a serialized index column as the index and sort by
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that in the resulting DataFrame.
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.. note::
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For non-bigquery engine, data is inlined in the query SQL if it is
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small enough (roughly 5MB or less in memory). Larger size data is
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loaded to a BigQuery table instead.
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**Examples:**
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>>> import bigframes.pandas as bpd

third_party/bigframes_vendored/pandas/io/pickle.py

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@@ -25,6 +25,11 @@ def read_pickle(
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If the content of the pickle file is a Series and its name attribute is None,
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the name will be set to '0' by default.
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.. note::
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Data is inlined in the query SQL if it is small enough (roughly 5MB
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or less in memory). Larger size data is loaded to a BigQuery table
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instead.
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**Examples:**
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>>> import bigframes.pandas as bpd

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