--- license: cc-by-4.0 pretty_name: Argo-Bench language: - en tags: - synthetic - text-to-sql - data-analysis - agents - benchmark - warehouse size_categories: - 1B/*.parquet the rows (monthly parts 2024-MM.parquet, or part-0.parquet) data//_delta_log/ a Delta Lake log over the same files (relative paths) tables.json every table: rows, files, column types, partition, cluster keys setup/ loaders and month views per engine (below) ``` Every column has one of six types, the same in every engine: | `tables.json` type | Parquet | BigQuery | Snowflake | Spark / Delta | Trino | Iceberg | |---|---|---|---|---|---|---| | `INT64` | int64 | INT64 | NUMBER(19,0) | BIGINT | bigint | long | | `FLOAT64` | double | FLOAT64 | FLOAT | DOUBLE | double | double | | `STRING` | string | STRING | VARCHAR | STRING | varchar | string | | `DATETIME` | timestamp[us], no zone | DATETIME | TIMESTAMP_NTZ(6) | TIMESTAMP_NTZ | timestamp(6) | timestamp | | `DATE` | date32 | DATE | DATE | DATE | date | date | | `BOOLEAN` | bool | BOOL | BOOLEAN | BOOLEAN | boolean | boolean | Timestamps are wall-clock times with no zone. Table and column names are upper case. Keep them that way: queries and the month views quote them. ## Get the files ```bash pip install -U "huggingface_hub[hf_xet]" hf download textql/Argo-Bench --repo-type dataset --local-dir argo-bench # or a few tables: hf download textql/Argo-Bench --repo-type dataset --local-dir argo-bench \ --include "data/GL_PERIODS/*" --include "tables.json" --include "setup/*" ``` The SQL files under `setup/` refer to the `data/` directory of your copy as `__DATA_ROOT__`. Fill it in once for the engine you use, for example: ```bash sed -i.bak 's#__DATA_ROOT__#s3://my-bucket/argo-bench/data#g' setup/spark/register_delta.sql ``` Every engine below reads the same Parquet files. Loading into BigQuery or Snowflake copies them into that warehouse. Delta Lake, Iceberg, Trino and DuckDB read them in place. ## DuckDB (no download needed) ```bash sed 's#__DATA_ROOT__#hf://datasets/textql/Argo-Bench/data#g' setup/duckdb/views.sql > views.sql duckdb argo.duckdb -c ".read views.sql" -c ".read setup/duckdb/month_views.sql" duckdb argo.duckdb -c 'SELECT COUNT(*) FROM food_delivery."XX_DISPUTES"' ``` Over `hf://` the base views take about 2 minutes and the month views about 7 (DuckDB reads Parquet footers over HTTP as it binds each view). Only the rows a query touches are fetched. Point `__DATA_ROOT__` at a local `data/` directory to make both near-instant. DuckDB can also read the Delta tables: `SELECT * FROM delta_scan('argo-bench/data/GL_PERIODS')`. ## BigQuery BigQuery loads from Google Cloud Storage, so copy `data/` into a bucket first. Use a bucket in (or inside) your dataset's location. Load jobs are free. The loaded dataset holds about 880 GiB of logical storage. ```bash gcloud storage cp -r argo-bench/data gs://my-bucket/argo-bench/ RELEASE_URI=gs://my-bucket/argo-bench BQ_PROJECT=my-project BQ_DATASET=food_delivery \ bash setup/bigquery/load.sh BQ_PROJECT=my-project BQ_DATASET=food_delivery bash setup/bigquery/month_views.sh ``` `load.sh` creates each table with its final types and loads it with one Parquet load job. 94 tables are MONTH-partitioned on the column the month views cut on, so a month view scans only its months, and the 12 most-scanned are clustered on the columns queries filter and join them on (`clustered_by` in `tables.json`). `JOBS=N` loads N tables at a time (default 8), `ONLY=A,B` just those tables, and `BQ_LOCATION` defaults to `US`. With `AUTHORIZE=1`, `month_views.sh` also makes each month dataset an authorized dataset on the base, so a reader granted only `food_delivery_6` cannot read past June (needs `jq`). ## Snowflake Create a stage named `"food_delivery"."ARGO_BENCH"` whose root holds `data/`, then run `load.sql` and `month_views.sql` in a database of your choice. - **Your copy in S3, GCS or Azure** (external stage): ```sql USE DATABASE my_db; CREATE SCHEMA IF NOT EXISTS "food_delivery"; CREATE STAGE "food_delivery"."ARGO_BENCH" URL = 's3://my-bucket/argo-bench/' STORAGE_INTEGRATION = my_integration; ``` - **A local download** (internal stage): fill in `__LOCAL_ROOT__` in `setup/snowflake/put.sql`, then `snowsql -d my_db -f setup/snowflake/put.sql`. ```bash snowsql -d my_db -f setup/snowflake/load.sql snowsql -d my_db -f setup/snowflake/month_views.sql ``` (`snow sql -f ...` with the Snowflake CLI works too.) `load.sql` creates each table with its final types, then runs one `COPY INTO ... MATCH_BY_COLUMN_NAME = CASE_SENSITIVE` per table. The schema name is the quoted, lower-case `"food_delivery"`. ## Delta Lake (Databricks, Spark, delta-rs) Each `data/
/` is already a Delta table. Its log names the files by relative path, so it works wherever the directory is copied: local disk, S3, GCS, ADLS, or a Databricks volume. Register the tables and add the month views: ```bash sed -i.bak 's#__DATA_ROOT__#s3://my-bucket/argo-bench/data#g' setup/spark/register_delta.sql # Databricks: run both files in a SQL editor or notebook, in the catalog you want. spark-sql --packages io.delta:delta-spark_2.13:4.0.0 \ --conf spark.sql.extensions=io.delta.sql.DeltaSparkSessionExtension \ --conf spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog \ -f setup/spark/register_delta.sql # then the same with -f setup/spark/month_views.sql ``` Delta tables with timestamps use the `timestampNtz` table feature (reader version 3), which Databricks Runtime 13.3+, Delta 3+, delta-rs and DuckDB support. From Python, without Spark: `deltalake.DeltaTable("argo-bench/data/XX_DISPUTES").to_pyarrow_table()`. ## Iceberg Iceberg metadata names files by absolute path, so it is written for your copy where it lives. `setup/iceberg/register.py` creates each table from its Parquet schema and adds the existing files (`pyiceberg` `add_files`: manifests, statistics and a name mapping are written, and no data is copied): ```bash pip install "pyiceberg[pyarrow,sql-sqlite]" # local copy, local SQLite catalog in ./iceberg/ python setup/iceberg/register.py --root argo-bench # a copy in object storage, into your catalog (REST, Glue, Hive, SQL, ...) python setup/iceberg/register.py --root s3://my-bucket/argo-bench \ --catalog prod -P type=rest -P uri=https://catalog.example.com -P warehouse=wh ``` Then query `food_delivery.
` from any engine attached to that catalog (Spark, Trino, Snowflake, DuckDB, PyIceberg). `setup/spark/month_views.sql` and `setup/trino/month_views.sql` create the month views in that catalog as well. ## Trino Trino reads the Delta tables in place through its Delta Lake connector: 1. Copy `setup/trino/delta.properties` to `etc/catalog/delta.properties`. Set `local.location` to your download, or switch to the S3/GCS lines. Restart Trino. 2. Register the tables, then add the month views: ```bash sed -i.bak 's#__DATA_ROOT__#local:///data#g' setup/trino/register_delta.sql trino --catalog delta -f setup/trino/register_delta.sql trino --catalog delta -f setup/trino/month_views.sql trino --catalog delta --schema food_delivery --execute 'SELECT COUNT(*) FROM xx_disputes' ``` For an Iceberg catalog instead, register with `setup/iceberg/register.py` into a catalog Trino's Iceberg connector also uses (REST, Glue, Hive metastore, JDBC). Then run `month_views.sql` with `--catalog` set to it. ## Month views (as-of datasets) Tasks are posed as of the end of a month. The full-year tables are the base (`food_delivery`). Eleven sibling schemas hold views that cut every table to what existed at the end of each month: | schema | rows kept | |---|---| | `food_delivery_1` | before 2024-02-01 | | `food_delivery_2` | before 2024-03-01 | | `food_delivery_3` | before 2024-04-01 | | `food_delivery_4` | before 2024-05-01 | | `food_delivery_5` | before 2024-06-01 | | `food_delivery_6` | before 2024-07-01 | | `food_delivery_7` | before 2024-08-01 | | `food_delivery_8` | before 2024-09-01 | | `food_delivery_9` | before 2024-10-01 | | `food_delivery_10` | before 2024-11-01 | | `food_delivery_11` | before 2024-12-01 | | `food_delivery` | the whole year | A view keeps a row when its creation instant (for most tables `CREATION_DATE`, for some a table-specific column) falls before the cutoff. Reference tables pass through whole, a few tables are period-keyed, and a few are left out of the month schemas. Each engine's `month_views` file carries every table's exact rule. In BigQuery (with `AUTHORIZE=1`), Snowflake, Databricks Unity Catalog and Trino a view reads the base with its owner's privileges, so a role granted only one month schema can read that month and not the full year. ## Tables | prefix | tables | rows | |---|---|---| | `XX_` | 76 | 2,611,986,780 | | `XLA_` | 7 | 1,323,720,550 | | `GL_` | 14 | 895,849,826 | | `RA_` | 9 | 871,697,233 | | `AR_` | 13 | 767,720,837 | | `OE_` | 6 | 582,587,260 | | `ZX_` | 8 | 158,621,036 | | `HZ_` | 12 | 98,039,549 | | `CE_` | 10 | 96,091,788 | | `AP_` | 12 | 47,692,675 | | `OKS_` | 6 | 25,772,522 | | `OKC_` | 9 | 17,349,814 | | `IBY_` | 6 | 11,151,388 | | `MTL_` | 9 | 3,170,345 | | `QP_` | 5 | 137,928 | | `HR_` | 4 | 54,460 | | `FND_` | 29 | 17,417 |
All 235 tables | table | rows | columns | files | size | |---|---|---|---|---| | `AP_CHECKS_ALL` | 5,223,800 | 22 | 1 | 75.0 MiB | | `AP_HOLDS_ALL` | 29,106 | 14 | 1 | 492.2 KiB | | `AP_HOLD_CODES` | 13 | 11 | 1 | 3.8 KiB | | `AP_INVOICES_ALL` | 6,042,034 | 36 | 1 | 110.1 MiB | | `AP_INVOICE_DISTRIBUTIONS_ALL` | 7,042,852 | 19 | 1 | 27.8 MiB | | `AP_INVOICE_LINES_ALL` | 17,487,560 | 17 | 1 | 121.3 MiB | | `AP_INVOICE_PAYMENTS_ALL` | 5,626,734 | 15 | 1 | 69.5 MiB | | `AP_PAYMENT_SCHEDULES_ALL` | 6,042,034 | 13 | 1 | 54.7 MiB | | `AP_SUPPLIERS` | 99,268 | 33 | 1 | 2.1 MiB | | `AP_SUPPLIER_SITES_ALL` | 99,268 | 19 | 1 | 1.1 MiB | | `AP_TERMS_LINES` | 3 | 9 | 1 | 3.1 KiB | | `AP_TERMS_TL` | 3 | 11 | 1 | 3.5 KiB | | `AR_ADJUSTMENTS_ALL` | 163,136 | 25 | 12 | 1.3 MiB | | `AR_AGING_BUCKETS` | 1 | 9 | 1 | 2.9 KiB | | `AR_AGING_BUCKET_LINES_B` | 5 | 11 | 1 | 3.8 KiB | | `AR_AGING_BUCKET_LINES_TL` | 5 | 9 | 1 | 3.0 KiB | | `AR_BATCHES_ALL` | 387 | 22 | 12 | 101.4 KiB | | `AR_CASH_RECEIPTS_ALL` | 85,814,307 | 39 | 12 | 743.4 MiB | | `AR_CASH_RECEIPT_HISTORY_ALL` | 257,640,459 | 25 | 12 | 1.8 GiB | | `AR_DISTRIBUTIONS_ALL` | 158,862,992 | 12 | 12 | 830.7 MiB | | `AR_PAYMENT_SCHEDULES_ALL` | 174,385,419 | 29 | 24 | 2.3 GiB | | `AR_RECEIPT_CLASSES` | 1 | 12 | 1 | 3.8 KiB | | `AR_RECEIPT_METHODS` | 2 | 9 | 1 | 3.2 KiB | | `AR_RECEIVABLES_TRX_ALL` | 3 | 12 | 1 | 4.0 KiB | | `AR_RECEIVABLE_APPLICATIONS_ALL` | 90,854,120 | 27 | 12 | 1.1 GiB | | `CE_BANK_ACCOUNTS` | 1 | 34 | 1 | 10.6 KiB | | `CE_BANK_ACCT_USES_ALL` | 1 | 21 | 1 | 6.2 KiB | | `CE_GL_ACCOUNTS_CCID` | 1 | 13 | 1 | 4.2 KiB | | `CE_STATEMENT_HEADERS` | 251 | 20 | 1 | 19.1 KiB | | `CE_STATEMENT_HEADERS_INT` | 0 | 13 | 1 | 1.6 KiB | | `CE_STATEMENT_LINES` | 5,378,573 | 19 | 12 | 41.2 MiB | | `CE_STATEMENT_LINES_INTERFACE` | 0 | 14 | 1 | 1.6 KiB | | `CE_STATEMENT_RECONCILS_ALL` | 90,712,954 | 18 | 12 | 357.3 MiB | | `CE_SYSTEM_PARAMETERS` | 1 | 16 | 1 | 5.1 KiB | | `CE_TRANSACTION_CODES` | 6 | 16 | 1 | 5.1 KiB | | `FND_APPLICATION` | 12 | 9 | 1 | 3.3 KiB | | `FND_APPLICATION_TL` | 12 | 9 | 1 | 3.2 KiB | | `FND_CONCURRENT_PROGRAMS` | 7 | 10 | 1 | 3.5 KiB | | `FND_CONCURRENT_PROGRAMS_TL` | 7 | 11 | 1 | 4.1 KiB | | `FND_CONCURRENT_REQUESTS` | 15,764 | 13 | 1 | 265.3 KiB | | `FND_CURRENCIES` | 68 | 11 | 1 | 4.4 KiB | | `FND_CURRENCIES_TL` | 68 | 9 | 1 | 3.8 KiB | | `FND_FLEX_HIERARCHIES` | 2 | 8 | 1 | 2.8 KiB | | `FND_FLEX_HIERARCHIES_TL` | 2 | 11 | 1 | 4.1 KiB | | `FND_FLEX_VALIDATION_QUALIFIERS` | 5 | 6 | 1 | 2.3 KiB | | `FND_FLEX_VALUES` | 351 | 18 | 1 | 10.9 KiB | | `FND_FLEX_VALUES_TL` | 351 | 10 | 1 | 10.3 KiB | | `FND_FLEX_VALUE_HIERARCHIES` | 33 | 11 | 1 | 3.7 KiB | | `FND_FLEX_VALUE_NORM_HIERARCHY` | 26 | 12 | 1 | 4.5 KiB | | `FND_FLEX_VALUE_SETS` | 7 | 11 | 1 | 3.9 KiB | | `FND_ID_FLEXS` | 1 | 14 | 1 | 4.7 KiB | | `FND_ID_FLEX_SEGMENTS` | 7 | 17 | 1 | 5.5 KiB | | `FND_ID_FLEX_SEGMENTS_TL` | 7 | 13 | 1 | 4.3 KiB | | `FND_ID_FLEX_STRUCTURES` | 1 | 14 | 1 | 4.6 KiB | | `FND_ID_FLEX_STRUCTURES_TL` | 1 | 12 | 1 | 4.1 KiB | | `FND_LANGUAGES` | 29 | 10 | 1 | 3.9 KiB | | `FND_LOOKUP_TYPES` | 74 | 10 | 1 | 5.2 KiB | | `FND_LOOKUP_TYPES_TL` | 74 | 12 | 1 | 7.1 KiB | | `FND_LOOKUP_VALUES` | 293 | 13 | 1 | 8.4 KiB | | `FND_RESPONSIBILITY` | 8 | 12 | 1 | 4.3 KiB | | `FND_RESPONSIBILITY_TL` | 8 | 10 | 1 | 3.5 KiB | | `FND_TERRITORIES` | 78 | 7 | 1 | 2.6 KiB | | `FND_TERRITORIES_TL` | 78 | 9 | 1 | 3.8 KiB | | `FND_USER` | 43 | 10 | 1 | 4.7 KiB | | `GL_ACCOUNT_HIERARCHIES` | 49,294 | 7 | 1 | 346.3 KiB | | `GL_BALANCES` | 198,553 | 22 | 1 | 3.2 MiB | | `GL_CODE_COMBINATIONS` | 10,666 | 19 | 1 | 74.6 KiB | | `GL_IMPORT_REFERENCES` | 893,825,932 | 17 | 36 | 7.4 GiB | | `GL_INTERFACE` | 0 | 17 | 1 | 1.8 KiB | | `GL_JE_BATCHES` | 2,897 | 15 | 36 | 210.5 KiB | | `GL_JE_CATEGORIES_TL` | 9 | 10 | 1 | 3.4 KiB | | `GL_JE_HEADERS` | 3,913 | 19 | 36 | 268.7 KiB | | `GL_JE_LINES` | 1,758,419 | 17 | 36 | 16.6 MiB | | `GL_JE_SOURCES_TL` | 9 | 15 | 1 | 4.9 KiB | | `GL_LEDGERS` | 1 | 45 | 1 | 13.8 KiB | | `GL_PERIODS` | 26 | 17 | 1 | 6.3 KiB | | `GL_PERIOD_STATUSES` | 104 | 20 | 1 | 9.2 KiB | | `GL_SUMMARY_TEMPLATES` | 3 | 21 | 1 | 7.0 KiB | | `HR_ALL_ORGANIZATION_UNITS` | 18,155 | 16 | 1 | 356.9 KiB | | `HR_LOCATIONS_ALL` | 18,152 | 17 | 1 | 471.9 KiB | | `HR_OPERATING_UNITS` | 1 | 6 | 1 | 2.0 KiB | | `HR_ORGANIZATION_INFORMATION` | 18,152 | 14 | 1 | 321.3 KiB | | `HZ_CODE_ASSIGNMENTS` | 28 | 18 | 1 | 6.1 KiB | | `HZ_CONTACT_POINTS` | 8,453,222 | 18 | 1 | 152.8 MiB | | `HZ_CUSTOMER_PROFILES` | 4,208,292 | 22 | 1 | 37.0 MiB | | `HZ_CUST_ACCOUNTS` | 4,208,292 | 14 | 1 | 40.4 MiB | | `HZ_CUST_ACCOUNT_ROLES` | 0 | 15 | 1 | 1.7 KiB | | `HZ_CUST_ACCT_SITES_ALL` | 18,679,554 | 17 | 1 | 278.3 MiB | | `HZ_CUST_PROFILE_CLASSES` | 1 | 21 | 1 | 6.1 KiB | | `HZ_CUST_SITE_USES_ALL` | 22,887,846 | 17 | 1 | 328.4 MiB | | `HZ_LOCATIONS` | 16,578,838 | 34 | 1 | 352.9 MiB | | `HZ_ORGANIZATION_PROFILES` | 18,181 | 17 | 1 | 404.4 KiB | | `HZ_PARTIES` | 4,307,589 | 31 | 1 | 121.2 MiB | | `HZ_PARTY_SITES` | 18,697,706 | 15 | 1 | 269.3 MiB | | `IBY_DOCS_PAYABLE_ALL` | 5,626,734 | 31 | 1 | 131.1 MiB | | `IBY_EXTERNAL_PAYEES_ALL` | 99,268 | 12 | 1 | 1.2 MiB | | `IBY_EXT_BANK_ACCOUNTS` | 99,323 | 18 | 1 | 1.3 MiB | | `IBY_PAYMENTS_ALL` | 5,223,800 | 34 | 1 | 86.5 MiB | | `IBY_PAY_INSTRUCTIONS_ALL` | 1,077 | 23 | 1 | 28.6 KiB | | `IBY_PMT_INSTR_USES_ALL` | 101,186 | 14 | 1 | 1.3 MiB | | `MTL_CATEGORIES_B` | 70 | 10 | 1 | 4.0 KiB | | `MTL_CATEGORIES_TL` | 70 | 9 | 1 | 3.7 KiB | | `MTL_CATEGORY_SETS_B` | 1 | 11 | 1 | 3.7 KiB | | `MTL_CATEGORY_SETS_TL` | 1 | 9 | 1 | 3.0 KiB | | `MTL_ITEM_CATEGORIES` | 1,050,683 | 13 | 1 | 3.0 MiB | | `MTL_PARAMETERS` | 18,153 | 12 | 1 | 159.9 KiB | | `MTL_SYSTEM_ITEMS_B` | 1,050,683 | 32 | 1 | 7.1 MiB | | `MTL_SYSTEM_ITEMS_TL` | 1,050,683 | 10 | 1 | 5.2 MiB | | `MTL_UNITS_OF_MEASURE_TL` | 1 | 17 | 1 | 4.8 KiB | | `OE_ORDER_HEADERS_ALL` | 81,021,428 | 41 | 12 | 2.9 GiB | | `OE_ORDER_LINES_ALL` | 448,369,838 | 24 | 12 | 4.4 GiB | | `OE_ORDER_SOURCES` | 40 | 12 | 1 | 5.7 KiB | | `OE_PRICE_ADJUSTMENTS` | 53,195,946 | 35 | 12 | 610.5 MiB | | `OE_TRANSACTION_TYPES_ALL` | 4 | 13 | 1 | 4.2 KiB | | `OE_TRANSACTION_TYPES_TL` | 4 | 13 | 1 | 4.3 KiB | | `OKC_K_HEADERS_ALL_B` | 1,625,449 | 53 | 1 | 32.1 MiB | | `OKC_K_HEADERS_TL` | 1,625,449 | 11 | 1 | 16.7 MiB | | `OKC_K_ITEMS` | 2,532,368 | 21 | 1 | 41.1 MiB | | `OKC_K_LINES_B` | 2,532,368 | 49 | 1 | 65.3 MiB | | `OKC_K_LINES_TL` | 2,532,368 | 11 | 1 | 26.8 MiB | | `OKC_K_PARTY_ROLES_B` | 3,250,898 | 17 | 1 | 76.4 MiB | | `OKC_K_PARTY_ROLES_TL` | 3,250,898 | 9 | 1 | 34.5 MiB | | `OKC_STATUSES_B` | 8 | 11 | 1 | 3.6 KiB | | `OKC_STATUSES_TL` | 8 | 11 | 1 | 3.4 KiB | | `OKS_BILL_CONT_LINES` | 5,927,298 | 33 | 12 | 33.1 MiB | | `OKS_BILL_TXN_LINES` | 5,927,298 | 18 | 12 | 29.0 MiB | | `OKS_K_LINES_B` | 2,532,368 | 29 | 1 | 48.2 MiB | | `OKS_K_LINES_TL` | 2,532,368 | 10 | 1 | 26.8 MiB | | `OKS_LEVEL_ELEMENTS` | 6,320,822 | 19 | 1 | 65.6 MiB | | `OKS_STREAM_LEVELS_B` | 2,532,368 | 24 | 1 | 45.6 MiB | | `QP_LIST_HEADERS_B` | 34,330 | 29 | 1 | 520.5 KiB | | `QP_LIST_HEADERS_TL` | 34,330 | 9 | 1 | 491.3 KiB | | `QP_LIST_LINES` | 34,579 | 33 | 1 | 523.6 KiB | | `QP_PRICING_ATTRIBUTES` | 34,687 | 23 | 1 | 461.7 KiB | | `QP_QUALIFIERS` | 2 | 24 | 1 | 7.2 KiB | | `RA_BATCH_SOURCES_ALL` | 3 | 10 | 1 | 3.6 KiB | | `RA_CUSTOMER_TRX_ALL` | 88,898,632 | 26 | 12 | 1.1 GiB | | `RA_CUSTOMER_TRX_LINES_ALL` | 536,593,468 | 20 | 12 | 5.0 GiB | | `RA_CUST_TRX_LINE_GL_DIST_ALL` | 246,205,117 | 20 | 12 | 1.8 GiB | | `RA_CUST_TRX_TYPES_ALL` | 4 | 20 | 1 | 6.1 KiB | | `RA_INTERFACE_LINES_ALL` | 0 | 18 | 1 | 2.1 KiB | | `RA_TERMS_B` | 3 | 12 | 1 | 3.9 KiB | | `RA_TERMS_LINES` | 3 | 9 | 1 | 3.2 KiB | | `RA_TERMS_TL` | 3 | 10 | 1 | 3.3 KiB | | `XLA_AE_HEADERS` | 166,707,354 | 22 | 13 | 639.6 MiB | | `XLA_AE_LINES` | 412,110,961 | 25 | 13 | 5.0 GiB | | `XLA_DISTRIBUTION_LINKS` | 412,110,961 | 7 | 13 | 1.9 GiB | | `XLA_EVENTS` | 166,707,354 | 18 | 13 | 463.5 MiB | | `XLA_EVENT_TYPES_B` | 6 | 12 | 1 | 4.0 KiB | | `XLA_EVENT_TYPES_TL` | 6 | 13 | 1 | 4.5 KiB | | `XLA_TRANSACTION_ENTITIES` | 166,083,908 | 12 | 13 | 397.6 MiB | | `XX_AUDIT_TRAIL` | 278,378 | 21 | 1 | 6.6 MiB | | `XX_CAMPAIGN_AUTHORITY_EVENTS` | 83,035 | 15 | 1 | 1.5 MiB | | `XX_CAMPAIGN_BUDGET_CREDITS` | 34,119 | 20 | 12 | 1.0 MiB | | `XX_CARD_FINGERPRINTS` | 7,510,260 | 12 | 1 | 209.6 MiB | | `XX_CARD_VERIFICATIONS` | 2,737,285 | 21 | 1 | 63.5 MiB | | `XX_COURIER_ACCOUNT_EVENTS` | 9,898 | 8 | 12 | 159.6 KiB | | `XX_COURIER_APPLICATIONS` | 40,131 | 8 | 12 | 639.2 KiB | | `XX_COURIER_APP_SESSIONS` | 6,073,139 | 9 | 12 | 75.8 MiB | | `XX_COURIER_DEVICES` | 115,332 | 6 | 12 | 788.6 KiB | | `XX_COURIER_EARNINGS` | 69,809,732 | 15 | 12 | 1.2 GiB | | `XX_COURIER_IDENTITY_CHECKS` | 154,501 | 11 | 12 | 2.6 MiB | | `XX_COURIER_VIOLATIONS` | 115,684 | 9 | 12 | 1.9 MiB | | `XX_COURIER_WAITS` | 21,853,896 | 22 | 12 | 714.4 MiB | | `XX_CUSTOMER_ACCOUNT_EVENTS` | 911,979 | 20 | 12 | 23.9 MiB | | `XX_CUSTOMER_DEVICES` | 9,779,781 | 13 | 1 | 148.7 MiB | | `XX_CUSTOMER_SESSIONS` | 283,610,657 | 16 | 12 | 4.3 GiB | | `XX_DELIVERY_ASSIGNMENTS` | 73,117,923 | 11 | 12 | 1.2 GiB | | `XX_DELIVERY_ATTEMPTS` | 1,976,574 | 17 | 12 | 31.5 MiB | | `XX_DELIVERY_LEGS` | 69,809,732 | 26 | 12 | 3.4 GiB | | `XX_DEVICES` | 9,396,417 | 13 | 1 | 260.6 MiB | | `XX_DISPATCH_ASSIGNMENTS` | 125,267,766 | 18 | 12 | 1.9 GiB | | `XX_DISPUTES` | 58,336 | 17 | 12 | 1.3 MiB | | `XX_DRIVER_LOCATION_OBSERVATIONS` | 134,680,131 | 8 | 12 | 1.3 GiB | | `XX_DRIVER_PROFILES` | 81,116 | 18 | 1 | 1.1 MiB | | `XX_DRIVER_QUESTS` | 145,577 | 16 | 1 | 1.8 MiB | | `XX_DRIVER_SHIFTS` | 6,100,182 | 15 | 12 | 118.2 MiB | | `XX_ENFORCEMENT_ACTIONS` | 11,321 | 17 | 1 | 71.4 KiB | | `XX_EXPERIMENT_ASSIGNMENTS` | 8,152 | 24 | 12 | 329.3 KiB | | `XX_FRAUD_WARNINGS` | 23,812 | 16 | 12 | 760.6 KiB | | `XX_GL_INTERFACE_HIST` | 481,714,971 | 9 | 36 | 1.6 GiB | | `XX_HOTSPOT_SNAPSHOTS` | 109,285 | 7 | 12 | 403.8 KiB | | `XX_INCENTIVE_COMMITMENTS` | 51,900,211 | 26 | 12 | 1.6 GiB | | `XX_INGESTION_RUNS` | 15,130 | 19 | 1 | 306.4 KiB | | `XX_INTEGRATION_INCIDENTS` | 24,718 | 15 | 12 | 590.6 KiB | | `XX_INTERFACE_ERRORS` | 2,269 | 20 | 1 | 61.2 KiB | | `XX_IP_ADDRESSES` | 2,653,306 | 17 | 1 | 19.5 MiB | | `XX_LOGIN_ATTEMPTS` | 33,413,381 | 15 | 12 | 669.0 MiB | | `XX_MARKETPLACE_ESTIMATES` | 2,489,706 | 22 | 12 | 36.5 MiB | | `XX_MEMBERSHIP_EVENTS` | 21,477,261 | 19 | 12 | 360.7 MiB | | `XX_MEMBERSHIP_ORDER_BENEFITS` | 44,503,426 | 19 | 12 | 690.4 MiB | | `XX_MERCHANT_CLOSURES` | 367,222 | 17 | 1 | 4.8 MiB | | `XX_MERCHANT_HANDOFF_CONFIRMATIONS` | 28,005,435 | 6 | 12 | 294.6 MiB | | `XX_MERCHANT_HOLIDAY_HOURS` | 90,760 | 14 | 1 | 690.2 KiB | | `XX_MERCHANT_HOURS` | 127,064 | 15 | 1 | 894.0 KiB | | `XX_MERCHANT_INTEGRATIONS` | 18,152 | 23 | 1 | 339.4 KiB | | `XX_MERCHANT_OPS_ACTIONS` | 3,373 | 26 | 12 | 191.6 KiB | | `XX_MERCHANT_RATING_SNAPSHOTS` | 5,074,486 | 14 | 12 | 18.2 MiB | | `XX_MERCHANT_READY_REPORTS` | 79,271,817 | 20 | 12 | 1.1 GiB | | `XX_MERCHANT_REGULATORY_EVENTS` | 12,602 | 15 | 1 | 204.1 KiB | | `XX_ORDER_PREP_QUOTES` | 81,021,428 | 16 | 12 | 1.0 GiB | | `XX_ORDER_PROMISES` | 71,853,206 | 3 | 12 | 421.0 MiB | | `XX_ORDER_REJECTIONS` | 428,752 | 18 | 12 | 8.0 MiB | | `XX_ORDER_STATUS_HIST` | 482,707,811 | 13 | 12 | 2.1 GiB | | `XX_PAYMENT_AUTHS` | 86,145,522 | 16 | 12 | 1.5 GiB | | `XX_PAYMENT_INSTRUMENTS` | 7,482,590 | 16 | 1 | 131.5 MiB | | `XX_PAYOUT_PERIODS` | 499 | 16 | 1 | 18.2 KiB | | `XX_PAY_PERIOD_INCENTIVES` | 53 | 32 | 1 | 16.8 KiB | | `XX_PREP_ESTIMATE_LOG` | 36,741,875 | 18 | 12 | 1.0 GiB | | `XX_PROMOTION_ALLOCATIONS` | 27,881,500 | 18 | 12 | 341.9 MiB | | `XX_PROMOTION_CHECKOUTS` | 99,171,094 | 11 | 12 | 1.2 GiB | | `XX_PROMOTION_CONTACTS` | 25,096,871 | 12 | 12 | 237.3 MiB | | `XX_PROMOTION_DECISIONS` | 13,530 | 22 | 12 | 552.1 KiB | | `XX_PROMOTION_SUBMISSIONS` | 41,238,534 | 8 | 12 | 414.5 MiB | | `XX_PROMOTION_VARIANTS` | 224 | 14 | 1 | 9.7 KiB | | `XX_PROMO_ATTEMPTS` | 33,993,279 | 20 | 12 | 681.8 MiB | | `XX_PROMO_CODES` | 34,556 | 20 | 1 | 799.8 KiB | | `XX_QUEST_INVITATIONS` | 15,762,681 | 14 | 1 | 244.0 MiB | | `XX_QUEST_PROGRESS` | 5,211,942 | 17 | 1 | 43.6 MiB | | `XX_QUEST_WINDOWS` | 145,577 | 14 | 1 | 2.4 MiB | | `XX_REFERRALS` | 508,614 | 15 | 1 | 13.1 MiB | | `XX_REFUNDS` | 1,875,087 | 20 | 12 | 57.2 MiB | | `XX_REVIEWS` | 9,530,392 | 16 | 12 | 166.0 MiB | | `XX_SUPPLY_FORECASTS` | 568,764 | 22 | 1 | 17.1 MiB | | `XX_SUPPLY_SNAPSHOTS` | 1,974,276 | 8 | 12 | 8.5 MiB | | `XX_SUPPORT_CASES` | 7,364,176 | 30 | 12 | 188.2 MiB | | `XX_TIP_ADJUSTMENTS` | 164,526 | 14 | 12 | 3.0 MiB | | `ZX_LINES` | 79,310,515 | 21 | 12 | 407.2 MiB | | `ZX_LINES_DET_FACTORS` | 79,310,515 | 22 | 12 | 385.1 MiB | | `ZX_RATES_B` | 1 | 18 | 1 | 5.5 KiB | | `ZX_RATES_TL` | 1 | 9 | 1 | 3.0 KiB | | `ZX_REGIMES_B` | 1 | 13 | 1 | 4.1 KiB | | `ZX_REGIMES_TL` | 1 | 9 | 1 | 3.0 KiB | | `ZX_TAXES_B` | 1 | 15 | 1 | 4.6 KiB | | `ZX_TAXES_TL` | 1 | 9 | 1 | 3.0 KiB |
## License CC BY 4.0.