guptaakashdeep opened a new issue, #1884:
URL: https://github.com/apache/iceberg-python/issues/1884
### Apache Iceberg version
0.9.0 (latest release)
### Please describe the bug 🐞
## Issue:
`table.inspect.entries()` fails when table is MOR table and has Delete Files
present in it. Iceberg MOR Table is created via Apache Spark 3.5.0 with Iceberg
1.5.0 and it's being read via PyIceberg 0.9.0 using
`StaticTable.from_metadata()`.
### Stacktrace:
```bash
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[2], line 1
----> 1 table.inspect.entries()
File
~/Documents/project-repos/git-repos/lakehouse-health-analyzer/venv/lib/python3.12/site-packages/pyiceberg/table/inspect.py:208,
in InspectTable.entries(self, snapshot_id)
188 partition = entry.data_file.partition
189 partition_record_dict = {
190 field.name: partition[pos]
191 for pos, field in
enumerate(self.tbl.metadata.specs()[manifest.partition_spec_id].fields)
192 }
194 entries.append(
195 {
196 "status": entry.status.value,
197 "snapshot_id": entry.snapshot_id,
198 "sequence_number": entry.sequence_number,
199 "file_sequence_number": entry.file_sequence_number,
200 "data_file": {
201 "content": entry.data_file.content,
202 "file_path": entry.data_file.file_path,
203 "file_format": entry.data_file.file_format,
204 "partition": partition_record_dict,
205 "record_count": entry.data_file.record_count,
206 "file_size_in_bytes":
entry.data_file.file_size_in_bytes,
207 "column_sizes":
dict(entry.data_file.column_sizes),
--> 208 "value_counts":
dict(entry.data_file.value_counts),
209 "null_value_counts":
dict(entry.data_file.null_value_counts),
210 "nan_value_counts":
dict(entry.data_file.nan_value_counts),
211 "lower_bounds": entry.data_file.lower_bounds,
212 "upper_bounds": entry.data_file.upper_bounds,
213 "key_metadata": entry.data_file.key_metadata,
214 "split_offsets": entry.data_file.split_offsets,
215 "equality_ids": entry.data_file.equality_ids,
216 "sort_order_id": entry.data_file.sort_order_id,
217 "spec_id": entry.data_file.spec_id,
218 },
219 "readable_metrics": readable_metrics,
220 }
221 )
223 return pa.Table.from_pylist(
224 entries,
225 schema=entries_schema,
226 )
TypeError: 'NoneType' object is not iterable
```
## Replication
This issue can be replicated by following the instructions below:
1. Create an Iceberg MOR table using `Spark 3.5.0` with `Iceberg 1.5.0`
```python
from pyspark.sql import SparkSession
from pyspark.sql.functions import lit, array, rand
DW_PATH='../warehouse'
spark = SparkSession.builder \
.master("local[4]") \
.appName("iceberg-mor-test") \
.config('spark.jars.packages',
'org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.5.0,org.apache.spark:spark-avro_2.12:3.5.0')\
.config('spark.sql.extensions','org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions')\
.config('spark.sql.catalog.local','org.apache.iceberg.spark.SparkCatalog') \
.config('spark.sql.catalog.local.type','hadoop') \
.config('spark.sql.catalog.local.warehouse',DW_PATH) \
.getOrCreate()
t1 = spark.range(10000).withColumn("year", lit(2023))
t1 = t1.withColumn("business_vertical",
array(lit("Retail"), lit("SME"), lit("Cor"),
lit("Analytics"))\
.getItem((rand()*4).cast("int")))
t1.coalesce(1).writeTo('local.db.pyic_mor_test').partitionedBy('year').using('iceberg')\
.tableProperty('format-version','2')\
.tableProperty('write.delete.mode','merge-on-read')\
.tableProperty('write.update.mode','merge-on-read')\
.tableProperty('write.merge.mode','merge-on-read')\
.create()
```
2. Checking Table Properties to make sure table is MOR
```python
spark.sql("SHOW TBLPROPERTIES local.db.pyic_mor_test").show(truncate=False)
```
```sql
+-------------------------------+-------------------+
|key |value |
+-------------------------------+-------------------+
|current-snapshot-id |2543645387796664537|
|format |iceberg/parquet |
|format-version |2 |
|write.delete.mode |merge-on-read |
|write.merge.mode |merge-on-read |
|write.parquet.compression-codec|zstd |
|write.update.mode |merge-on-read |
+-------------------------------+-------------------+
```
3. Running an `UPDATE` statement to generate a Delete File
```python
spark.sql(f"UPDATE local.db.pyic_mor_test SET business_vertical =
'DataEngineering' WHERE id > 7000")
```
4. Checking if Delete File is generated
```python
spark.table(f"local.db.pyic_mor_test.delete_files").show()
```
```sql
+-------+--------------------+-----------+-------+---------+------------+------------------+--------------------+------------+-----------------+----------------+--------------------+--------------------+------------+-------------+------------+-------------+--------------------+
|content|
file_path|file_format|spec_id|partition|record_count|file_size_in_bytes|
column_sizes|value_counts|null_value_counts|nan_value_counts|
lower_bounds|
upper_bounds|key_metadata|split_offsets|equality_ids|sort_order_id|
readable_metrics|
+-------+--------------------+-----------+-------+---------+------------+------------------+--------------------+------------+-----------------+----------------+--------------------+--------------------+------------+-------------+------------+-------------+--------------------+
| 1|/Users/akashdeepg...| PARQUET| 0| {2023}| 2999|
4878|{2147483546 -> 21...| NULL| NULL|
NULL|{2147483546 -> [2...|{2147483546 -> [2...| NULL| [4]|
NULL| NULL|{{NULL, NULL, NUL...|
+-------+--------------------+-----------+-------+---------+------------+------------------+--------------------+------------+-----------------+----------------+--------------------+--------------------+------------+-------------+------------+-------------+--------------------+
```
### Reading Spark created table from PyIceberg
```python
from pyiceberg.table import StaticTable
# Using latest metadata.json path
metadata_path = "./warehouse/db/pyic_mor_test/metadata/v2.metadata.json"
table = StaticTable.from_metadata(metadata_path)
# This will break with the stacktrace provided above
table.inspect.entries()
```
## Issue found after debugging
I did some debugging and figured out the `inspect.entries()` break for MOR
tables while reading the `*-delete.parquet` files present in table.
While reading the Delete file, `value_counts` is coming as null. I can see
that `ManifestEntryStatus` is `ADDED` and `DataFile` content is
`DataFileContent.POSITION_DELETES` which seems to be correct.
I further looked into the `manifest.avro` file that holds the entry for
delete parquet files. And well, `value_counts` populated there itself is
`NULL`. That's the reason `entry.data_file.value_counts` is coming as `null`.
`value_counts` as `null` can also be seen in above in the output of query of
`delete_files` table.
### Willingness to contribute
- [ ] I can contribute a fix for this bug independently
- [x] I would be willing to contribute a fix for this bug with guidance from
the Iceberg community
- [ ] I cannot contribute a fix for this bug at this time
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