|
42
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 42
}
show_string {
input {
common {
plan_id: 41
}
local_relation {
data: "\377\377\377\377@\000\000\000[truncated(size=152)]"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "9ea1da6f-1c79-4ccf-a929-919d1c218b33"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:46:19
|
2 ms
|
|
|
|
41
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 40
}
sql {
query: "drop table bronze.test.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "d8f4d58f-4887-4245-8286-25017dea280d"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:46:19
|
18 ms
|
|
|
|
40
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 39
}
show_string {
input {
common {
plan_id: 38
}
sql {
query: "SELECT * FROM bronze.test.test"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "2248dcd4-cdd8-4587-9d70-46153ea93a3c"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:46:02
|
48 ms
|
|
|
|
39
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 36
}
show_string {
input {
common {
plan_id: 35
}
local_relation {
data: "\377\377\377\377@\000\000\000[truncated(size=152)]"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "4adff194-29c4-40e7-8722-4faf3d4be733"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:45:57
|
2 ms
|
|
|
|
38
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 34
}
sql {
query: "TRUNCATE table bronze.test.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "2b0d76d7-75dc-4917-86c0-9253b4e5e80c"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:45:57
|
0.2 s
|
|
|
|
36
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 32
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "db4165ef-afeb-44ab-99fc-76c6de712efd"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:45:41
|
1 s
|
|
+details
|
|
|
| ID | Description | Submitted | Duration | Job IDs |
|
37
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 32
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "db4165ef-afeb-44ab-99fc-76c6de712efd"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:45:41
|
1 s
|
[19][20]
|
|
|
34
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 30
}
show_string {
input {
common {
plan_id: 29
}
local_relation {
data: "\377\377\377\377@\000\000\000[truncated(size=152)]"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "27dd2a78-2fa4-44ee-8a10-25fb6a9ca278"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:45:25
|
2 ms
|
|
|
|
33
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 28
}
sql {
query: "DROP table bronze.test.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "93e8a089-d82d-4d7d-b857-75a41570e454"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:45:25
|
20 ms
|
|
|
|
32
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 27
}
show_string {
input {
common {
plan_id: 26
}
sql {
query: "SELECT * FROM bronze.test.test"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "ec340348-af94-45c8-9987-018a67ac1f24"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:44:57
|
0.3 s
|
[18]
|
|
|
30
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 23
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "02e1d862-d2a1-47eb-8234-735f3dc89c10"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:44:54
|
1.0 s
|
|
+details
|
|
|
| ID | Description | Submitted | Duration | Job IDs |
|
31
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 23
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "02e1d862-d2a1-47eb-8234-735f3dc89c10"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:44:54
|
0.9 s
|
[16][17]
|
|
|
26
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 18
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "d9777848-021c-45ac-acb9-b2575596c989"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:41:33
|
1 s
|
|
+details
|
|
|
| ID | Description | Submitted | Duration | Job IDs |
|
27
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 18
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "d9777848-021c-45ac-acb9-b2575596c989"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:41:33
|
1 s
|
[14][15]
|
|
|
24
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 16
}
show_string {
input {
common {
plan_id: 15
}
local_relation {
data: "\377\377\377\377@\000\000\000[truncated(size=152)]"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "9176afd4-a030-4e74-8972-7ae029562688"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:38:39
|
2 ms
|
|
|
|
23
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 14
}
sql {
query: "drop table bronze.test.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "1d196cb7-8201-4a1e-818b-9fa406562ae3"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:38:39
|
49 ms
|
|
|
|
22
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 12
}
sql {
query: "drop table bronze.test.verify_sts"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "336a58a4-820d-42c2-9ba6-34532cff4a4f"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:38:04
|
71 ms
|
|
|
|
21
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 11
}
show_string {
input {
common {
plan_id: 10
}
sql {
query: "SELECT count(*), status FROM bronze.test.test GROUP BY status"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "c6b17976-e5fd-4d12-864f-e1d674bf95b7"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:36:30
|
1.0 s
|
[12][13]
|
|
|
19
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 7
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "533d10ac-4b22-4337-a0b9-3050b7fb6181"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:36:26
|
1.0 s
|
|
+details
|
|
|
| ID | Description | Submitted | Duration | Job IDs |
|
20
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 7
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "533d10ac-4b22-4337-a0b9-3050b7fb6181"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:36:26
|
0.9 s
|
[10][11]
|
|
|
18
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 5
}
sql {
query: "CREATE TABLE IF NOT EXISTS bronze.test.verify_sts (id INT) USING iceberg"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "e6980855-92ea-41b1-a0e1-92864d671d0c"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:36:24
|
0.5 s
|
|
|
|
17
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 3
}
sql {
query: "CREATE NAMESPACE IF NOT EXISTS bronze.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "069a403d-e9ba-47a0-b5c7-f904d468030a"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:36:22
|
78 ms
|
|
|
|
16
|
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "61ec31aa-ec60-4847-8384-fe1f77644a71"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 2
}
show_string {
input {
common {
plan_id: 1
}
sql {
query: "SELECT \'READY\' AS STATUS"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "f5df0598-1b71-4764-af9b-501ae2aece94"
client_observed_server_side_session_id: "6d58c63b-fd77-4e70-ac9c-f6d1a7db4baf"
|
2026/05/11 04:36:10
|
65 ms
|
[9]
|
|
|
14
|
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 5
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "99c0fa8d-d144-4286-9401-592967857868"
client_observed_server_side_session_id: "442b3d64-e5ae-4f9b-b202-9128f7c20e39"
|
2026/05/11 04:34:40
|
2 s
|
|
+details
|
|
|
| ID | Description | Submitted | Duration | Job IDs |
|
15
|
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 5
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "99c0fa8d-d144-4286-9401-592967857868"
client_observed_server_side_session_id: "442b3d64-e5ae-4f9b-b202-9128f7c20e39"
|
2026/05/11 04:34:40
|
1 s
|
[7][8]
|
|
|
13
|
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 3
}
sql {
query: "CREATE NAMESPACE IF NOT EXISTS bronze.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "875eb492-e7be-4e66-b9a6-30330230f4a4"
client_observed_server_side_session_id: "442b3d64-e5ae-4f9b-b202-9128f7c20e39"
|
2026/05/11 04:34:35
|
97 ms
|
|
|
|
12
|
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "4ab3976b-dcbe-4020-b06b-15c63f8fd1c7"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 2
}
show_string {
input {
common {
plan_id: 1
}
sql {
query: "SELECT \'READY\' AS STATUS"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "ab7f8859-b372-4654-9343-a053ef0091e3"
client_observed_server_side_session_id: "442b3d64-e5ae-4f9b-b202-9128f7c20e39"
|
2026/05/11 04:34:17
|
49 ms
|
[6]
|
|
|
11
|
Spark Connect - session_id: "c72cf9f2-3595-4d09-adfc-629a083c596a"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "c72cf9f2-3595-4d09-adfc-629a083c596a"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "c72cf9f2-3595-4d09-adfc-629a083c596a"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 2
}
show_string {
input {
common {
plan_id: 1
}
sql {
query: "SELECT \'READY\' AS STATUS"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "def49f09-1be4-46d3-82b9-d335721f6052"
client_observed_server_side_session_id: "d88c5c99-077f-462f-971c-f11c7e9be82e"
|
2026/05/11 04:31:36
|
74 ms
|
[5]
|
|
|
10
|
Spark Connect - session_id: "8c0de3c6-0219-44ff-b69c-319d15b20457"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "8c0de3c6-0219-44ff-b69c-319d15b20457"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "8c0de3c6-0219-44ff-b69c-319d15b20457"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 2
}
show_string {
input {
common {
plan_id: 1
}
sql {
query: "SELECT \'READY\' AS STATUS"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "5f32c8e2-abc0-4fce-ac15-2e36e070dfcb"
client_observed_server_side_session_id: "086a972b-c33f-4f80-ba0b-8c72fc6cda66"
|
2026/05/11 04:30:02
|
52 ms
|
[4]
|
|
|
8
|
Spark Connect - session_id: "f15d8ea2-f375-4431-9a62-15dfcf3e3fdd"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "f15d8ea2-f375-4431-9a62-15dfcf3e3fdd"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "f15d8ea2-f375-4431-9a62-15dfcf3e3fdd"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 2
}
show_string {
input {
common {
plan_id: 1
}
sql {
query: "SELECT \'READY\' AS STATUS"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "4ed01114-7e92-476a-ae13-ffe8e29fa58e"
client_observed_server_side_session_id: "23bd2d34-9233-41ce-883b-aa45af2684e2"
|
2026/05/11 04:26:52
|
79 ms
|
[3]
|
|
|
5
|
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 9
}
sql {
query: "CREATE NAMESPACE IF NOT EXISTS bronze.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "aeb95485-a5c4-46a9-8291-907172ec8e8c"
client_observed_server_side_session_id: "96aa90ce-5e9e-4fc3-9fb4-4c8f91f72a9e"
|
2026/05/11 04:25:36
|
18 ms
|
|
|
|
2
|
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 5
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "b788f1b9-91f2-49b1-ad43-edc15f0064f4"
client_observed_server_side_session_id: "96aa90ce-5e9e-4fc3-9fb4-4c8f91f72a9e"
|
2026/05/11 04:22:54
|
4 s
|
|
+details
|
|
|
| ID | Description | Submitted | Duration | Job IDs |
|
3
|
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 5
}
sql {
query: "\nCREATE TABLE bronze.test.test \nUSING iceberg \nAS\nWITH base_data AS (\n -- Generates 1,000 initial rows\n SELECT \n id as raw_id,\n uuid() as session_id,\n CAST(rand() * 10000 AS INT) as category_id,\n CASE WHEN rand() > 0.5 THEN \'ACTIVE\' ELSE \'INACTIVE\' END as status,\n current_timestamp() as ts\n FROM range(1000)\n),\nexploded_data AS (\n -- Cross join to explode 1,000 rows to 1,000,000 rows\n -- Increase the range(1000) to 10000 if you want 10M rows\n SELECT a.* \n FROM base_data a\n CROSS JOIN (SELECT id FROM range(1000)) b\n)\nSELECT \n raw_id,\n session_id,\n -- Complex hashing to stress CPU/Executors\n sha2(concat(CAST(raw_id AS STRING), session_id), 256) as record_hash,\n sha2(reverse(session_id), 512) as security_token,\n -- Analytical transformations\n category_id,\n status,\n ts,\n -- Add some junk data to increase file size (S3 stress)\n repeat(sha2(CAST(raw_id AS STRING), 256), 5) as padding_data\nFROM exploded_data;\n"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "b788f1b9-91f2-49b1-ad43-edc15f0064f4"
client_observed_server_side_session_id: "96aa90ce-5e9e-4fc3-9fb4-4c8f91f72a9e"
|
2026/05/11 04:22:55
|
4 s
|
[1][2]
|
|
|
1
|
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
+details
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
...
session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
command {
sql_command {
input {
common {
plan_id: 3
}
sql {
query: "CREATE NAMESPACE IF NOT EXISTS bronze.test"
}
}
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "6c53ae0d-7fb6-4eea-a202-88ef9df086f3"
client_observed_server_side_session_id: "96aa90ce-5e9e-4fc3-9fb4-4c8f91f72a9e"
|
2026/05/11 04:22:50
|
39 ms
|
|
|
|
0
|
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
+details
Spark Connect - session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
root {
common {
pla...
session_id: "968efe1c-80d2-4c9c-8f88-84933a24d214"
user_context {
user_id: "iqran"
}
plan {
root {
common {
plan_id: 2
}
show_string {
input {
common {
plan_id: 1
}
sql {
query: "SELECT \'READY\' AS STATUS"
}
}
num_rows: 20
truncate: 20
}
}
}
client_type: "_SPARK_CONNECT_PYTHON spark/4.1.1 os/darwin python/3.10.18"
request_options {
result_chunking_options {
allow_arrow_batch_chunking: true
}
}
request_options {
reattach_options {
reattachable: true
}
}
operation_id: "68fd2298-5078-401c-8551-f42b834e6a31"
client_observed_server_side_session_id: "96aa90ce-5e9e-4fc3-9fb4-4c8f91f72a9e"
|
2026/05/11 04:22:29
|
0.9 s
|
[0]
|
|