nl2sqlproj/spider2-nl2sql huggingface dataset:
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.imaging_level4_HTAPP_merfish_r4`
(
  iObs INT64 OPTIONS(description="Index to cell barcodes"),
  iVar INT64 OPTIONS(description="Index to gene IDs"),
  X_value FLOAT64 OPTIONS(description="Expression value for a given gene and cell"),
  featureID STRING OPTIONS(description="Cell barcode"),
  index STRING OPTIONS(description="Gene name"),
  Source_filename STRING OPTIONS(description="Name of file record was derived from"),
  Source_entityId STRING OPTIONS(description="Synapse ID of source file"),
  HTAN_Center STRING OPTIONS(description="Name of HTAN Center e.g. HTAN HTAPP"),
  HTAN_Data_File_ID STRING OPTIONS(description="Self-identifier for this data file - HTAN ID of this file HTAN ID SOP (eg HTANx_yyy_zzz)"),
  HTAN_Biospecimen_ID STRING OPTIONS(description="HTAN ID associated with a biosample based on HTAN ID SOP (eg HTANx_yyy_zzz)")
)
OPTIONS(
  friendly_name="HTAN HTAPP IMAGING LEVEL 4 DATA - MERFISH R4 VERSIONED",
  description="Data was derived in October 2023 from 12 MERFISH Imaging Level 4 csv files submitted by the HTAPP HTAN center.",
  labels=[("access", "open"), ("data_type", "cell_spatial_characterization"), ("program", "htan"), ("source", "htan-htapp"), ("category", "processed_-omics_data"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.imaging_level4_HTAPP_merfish_r4` (iObs, iVar, X_value, featureID, index, Source_filename, Source_entityId, HTAN_Center, HTAN_Data_File_ID, HTAN_Biospecimen_ID) VALUES (10168, 14, 1.0, '196309184612864059165772869392844126266', 'AR', 'counts_HTAPP-313_slice4.h5ad', 'syn25541295', 'HTAN HTAPP', 'HTA1_313_932304999400', 'HTA1_313_932304'), (5098, 14, 1.0, '264754635535196310561559389645283700310', 'AR', 'counts_HTAPP-313_slice4.h5ad', 'syn25541295', 'HTAN HTAPP', 'HTA1_313_932304999400', 'HTA1_313_932304'), (7460, 14, 1.0, '208982647981705978860240757190124152107', 'AR', 'counts_HTAPP-313_slice4.h5ad', 'syn25541295', 'HTAN HTAPP', 'HTA1_313_932304999400', 'HTA1_313_932304'), (11406, 14, 1.0, '336875273295537462619762930201123541717', 'AR', 'counts_HTAPP-313_slice4.h5ad', 'syn25541295', 'HTAN HTAPP', 'HTA1_313_932304999400', 'HTA1_313_932304'), (1796, 14, 2.0, '144061537522085061468810725486084690620', 'AR', 'counts_HTAPP-313_slice4.h5ad', 'syn25541295', 'HTAN HTAPP', 'HTA1_313_932304999400', 'HTA1_313_932304');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.scRNAseq_HTAPP_level4_r3`
(
  NAME STRING OPTIONS(description="Cell barcode"),
  X FLOAT64 OPTIONS(description="umap X coordinate"),
  Y FLOAT64 OPTIONS(description="umap Y coordinate"),
  Cell_Subset STRING OPTIONS(description="Cell Subset"),
  Biospecimen STRING OPTIONS(description="HTAN ID associated with a biosample based on HTAN ID SOP (eg HTANx_yyy_zzz)"),
  Source_filename STRING OPTIONS(description="Name of file record was derived from"),
  Source_entityId STRING OPTIONS(description="Synapse ID of source file"),
  HTAN_Center STRING OPTIONS(description="Name of HTAN Center"),
  CellType STRING OPTIONS(description="Cell type name"),
  HTAPP_ID STRING OPTIONS(description="HTAPP internal ID"),
  Top_Level_Cell_Subset STRING OPTIONS(description="Top level cell subset"),
  batchID STRING OPTIONS(description="Experimental run ID")
)
OPTIONS(
  friendly_name="HTAPP SCRNASEQ LEVEL 4 DATA R3 VERSIONED",
  description="Data was extracted in April 2023 from single cell level 4 TSV files submitted by the HTAPP HTAN Center. Table contains sample-level summary data encompassing 7 disease types.",
  labels=[("access", "open"), ("reference_genome", "hg38"), ("data_type", "gene_expression"), ("program", "htan"), ("source", "htan-htapp"), ("category", "processed_-omics_data"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.scRNAseq_HTAPP_level4_r3` (NAME, X, Y, Cell_Subset, Biospecimen, Source_filename, Source_entityId, HTAN_Center, CellType, HTAPP_ID, Top_Level_Cell_Subset, batchID) VALUES ('AAACCTGAGGCGCTCT-1', 6.574855177, -11.07746638, 'cM01 (Monocyte)', 'HTA1_272_4831101', 'crc10x_HTAPP_L4.tsv', 'syn26127158', 'HTAN HTAPP', NULL, 'HTAPP-272-SMP-4831', 'Myeloid', 'C143_T_1_1_0_c1_v2'), ('AAACCTGTCAGAGCTT-1', -6.979610594, -11.52081931, 'cB2 (B GC-like)', 'HTA1_272_4831101', 'crc10x_HTAPP_L4.tsv', 'syn26127158', 'HTAN HTAPP', NULL, 'HTAPP-272-SMP-4831', 'B', 'C143_T_1_1_0_c1_v2'), ('AAACGGGCAGCTGCTG-1', -6.462646268, -12.25508643, 'cB2 (B GC-like)', 'HTA1_272_4831101', 'crc10x_HTAPP_L4.tsv', 'syn26127158', 'HTAN HTAPP', NULL, 'HTAPP-272-SMP-4831', 'B', 'C143_T_1_1_0_c1_v2'), ('AAACGGGGTCCCTACT-1', -6.788758113, -12.18036142, 'cB2 (B GC-like)', 'HTA1_272_4831101', 'crc10x_HTAPP_L4.tsv', 'syn26127158', 'HTAN HTAPP', NULL, 'HTAPP-272-SMP-4831', 'B', 'C143_T_1_1_0_c1_v2'), ('AAACGGGGTGGCAAAC-1', -8.385639478, -6.617814025, 'cP2 (Plasma IgG)', 'HTA1_272_4831101', 'crc10x_HTAPP_L4.tsv', 'syn26127158', 'HTAN HTAPP', NULL, 'HTAPP-272-SMP-4831', 'Plasma', 'C143_T_1_1_0_c1_v2');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.metabolomics_metadata_r2_v2`
(
  Component STRING OPTIONS(description="Category of metadata (e.g. Diagnosis, Biospecimen, scRNA-seq Level 1, etc.); provide the same one for all items/rows."),
  Filename STRING OPTIONS(description="Name of a file"),
  File_Format STRING OPTIONS(description="Format of a file (e.g. txt, csv, fastq, bam, etc.)"),
  HTAN_Parent_Biospecimen_ID STRING OPTIONS(description="HTAN Biospecimen Identifier (eg HTANx_yyy_zzz) indicating the biospecimen(s) from which these files were derived; multiple parent biospecimen should be comma-separated"),
  HTAN_Data_File_ID STRING OPTIONS(description="Self-identifier for this data file - HTAN ID of this file HTAN ID SOP (eg HTANx_yyy_zzz)"),
  Assay_Type STRING OPTIONS(description="The type and level of assay this metadata applies to (e.g. RPPA, Nanostring DSP, etc.)"),
  entityId STRING OPTIONS(description="Synapse ID of entity"),
  HTAN_Center STRING OPTIONS(description="Name of HTAN Center e.g. HTAN HTAPP"),
  Data_Release STRING OPTIONS(description="Inclusion in HTAN Data Release e.g. Release 1.0"),
  File_Size INT64 OPTIONS(description="Size of file (bucket object) in bytes"),
  Base_Filename STRING OPTIONS(description="Base name of file"),
  md5 STRING OPTIONS(description="md5 hash of file")
)
OPTIONS(
  friendly_name="HTAN METABOLOMICS METADATA R2 VERSIONED",
  description="Data was extracted from HTAN Synapse projects in April 2022.",
  labels=[("access", "open"), ("data_type", "file_metadata"), ("program", "htan"), ("source", "htan"), ("status", "current"), ("category", "metadata")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.metabolomics_metadata_r2_v2` (Component, Filename, File_Format, HTAN_Parent_Biospecimen_ID, HTAN_Data_File_ID, Assay_Type, entityId, HTAN_Center, Data_Release, File_Size, Base_Filename, md5) VALUES ('OtherAssay', 'metabolomics/Batch 1/nHILIC/A001-C-005.raw', 'raw', 'HTA10_01_005', 'HTA10_01_00505001', 'LC-MS/MS', 'syn24167658', 'HTAN Stanford', 'Release 1.0', 258507293, 'A001-C-005.raw', '378b19c4be4de902867e2e654a294927'), ('OtherAssay', 'metabolomics/Batch 1/nRPLC/A001-C-005.raw', 'raw', 'HTA10_01_005', 'HTA10_01_00505002', 'LC-MS/MS', 'syn24167679', 'HTAN Stanford', 'Release 1.0', 85737472, 'A001-C-005.raw', '1d844d61928a2dd93035a74c8e0ffbec'), ('OtherAssay', 'metabolomics/Batch 1/pHILIC/A001-C-005.raw', 'raw', 'HTA10_01_005', 'HTA10_01_00505003', 'LC-MS/MS', 'syn24167748', 'HTAN Stanford', 'Release 1.0', 363268540, 'A001-C-005.raw', '493227cba379ca4ec75391009e47f7dc'), ('OtherAssay', 'metabolomics/Batch 1/pRPLC/A001-C-005.raw', 'raw', 'HTA10_01_005', 'HTA10_01_00505004', 'LC-MS/MS', 'syn24167794', 'HTAN Stanford', 'Release 1.0', 236267015, 'A001-C-005.raw', 'ee424d7be2a856efdf401eba7bc832f1'), ('OtherAssay', 'metabolomics/Batch 1/nHILIC/A001-C-007.raw', 'raw', 'HTA10_01_007', 'HTA10_01_00705001', 'LC-MS/MS', 'syn24167636', 'HTAN Stanford', 'Release 1.0', 258917088, 'A001-C-007.raw', '91af4159eb9861842ca1fe197a8746fa');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.id_provenance_r4`
(
  HTAN_Data_File_ID STRING OPTIONS(description="Self-identifier for this data file - HTAN ID of this file HTAN ID SOP (eg HTANx_yyy_zzz)"),
  HTAN_Assayed_Biospecimen_ID STRING OPTIONS(description="HTAN ID of the biospecimen directly assayed using the experimental platform"),
  HTAN_Parent_Data_File_ID STRING OPTIONS(description="HTAN Data File Identifier indicating the file(s) from which these files were derived"),
  Filename STRING OPTIONS(description="Name of a file"),
  entityId STRING OPTIONS(description="Synapse ID of entity"),
  Component STRING OPTIONS(description="Category of metadata (e.g. Diagnosis, Biospecimen, scRNA-seq Level 1, etc.)"),
  Data_Release STRING OPTIONS(description="Inclusion in HTAN Data Release e.g. Release 1.0"),
  CDS_Release STRING OPTIONS(description="CDS transfer package in which file was included e.g. v22.6.1.seq"),
  HTAN_Center STRING OPTIONS(description="Name of HTAN Center e.g. HTAN HTAPP"),
  HTAN_Originating_Biospecimen_ID STRING OPTIONS(description="HTAN ID of the biopsied or resected biospecimen from the patient from which the assay data were derived"),
  HTAN_Participant_ID STRING OPTIONS(description="HTAN ID associated with a patient based on HTAN ID SOP (eg HTANx_yyy )"),
  Biospecimen_Path STRING OPTIONS(description="Full Biospecimen ancestry path from HTAN_Assayed_Biospecimen_ID to HTAN_Originating_Biospecimen_ID as comma separated list")
)
OPTIONS(
  friendly_name="ID PROVENANCE TABLE R4 VERSIONED",
  description="This table contains biospecimen and participant IDs for each HTAN data file",
  labels=[("access", "open"), ("data_type", "file_metadata"), ("program", "htan"), ("source", "htan"), ("category", "metadata"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.id_provenance_r4` (HTAN_Data_File_ID, HTAN_Assayed_Biospecimen_ID, HTAN_Parent_Data_File_ID, Filename, entityId, Component, Data_Release, CDS_Release, HTAN_Center, HTAN_Originating_Biospecimen_ID, HTAN_Participant_ID, Biospecimen_Path) VALUES ('HTA9_1_1026', 'HTA9_1_1', NULL, 'bulk_dnaseq_level_1/dab2e9d0-78cb-4b44-bcd1-ed30b5d31bbf_R1.fq.gz', 'syn23640172', 'BulkWESLevel1', 'Release 1.0', 'v21.9.1.seq', 'HTAN OHSU', 'HTA9_1_1', 'HTA9_1', 'HTA9_1_1'), ('HTA9_1_1006', 'HTA9_1_1', NULL, 'bulk_dnaseq_level_1/8a049868-852c-484b-af34-d83686866090_R1.fq.gz', 'syn23639898', 'BulkWESLevel1', 'Release 1.0', 'v21.9.1.seq', 'HTAN OHSU', 'HTA9_1_1', 'HTA9_1', 'HTA9_1_1'), ('HTA9_1_1092', 'HTA9_1_1', NULL, 'bulk_dnaseq_level_1/9954a4e1-6d64-4edb-ab7e-ab5375545a80_R1.fq.gz', 'syn23639905', 'BulkWESLevel1', 'Release 1.0', 'v21.9.1.seq', 'HTAN OHSU', 'HTA9_1_1', 'HTA9_1', 'HTA9_1_1'), ('HTA9_1_1048', 'HTA9_1_1', NULL, 'bulk_dnaseq_level_1/c3a84e06-0005-4d2a-8cdc-abc453ebfd4e_R1.fq.gz', 'syn23640170', 'BulkWESLevel1', 'Release 1.0', 'v21.9.1.seq', 'HTAN OHSU', 'HTA9_1_1', 'HTA9_1', 'HTA9_1_1'), ('HTA9_1_1101', 'HTA9_1_1', NULL, 'bulk_dnaseq_level_1/8ee7beca-33b1-4603-944e-c67c1140737d_R1.fq.gz', 'syn23639919', 'BulkWESLevel1', 'Release 1.0', 'v21.9.1.seq', 'HTAN OHSU', 'HTA9_1_1', 'HTA9_1', 'HTA9_1_1');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.dataFileSynapseID_to_BigQueryTableID_map_r5`
(
  entityId STRING OPTIONS(description="Synapse ID of Entity"),
  bq_table_id STRING OPTIONS(description="BigQuery table ID in the format <project-name>.<dataset-name>.<table-name>")
)
OPTIONS(
  friendly_name="HTAN ASSAY FILE SYNAPSE ID TO CGC BIGQUERY TABLE ID MAP R5 VERSIONED",
  description="This table was generated in April 2024 and contains mapping information between assay tables available in Big Query and the relevant individual synapse entities that comprise them.",
  labels=[("access", "open"), ("data_type", "file_metadata"), ("program", "htan"), ("source", "htan"), ("category", "metadata"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.dataFileSynapseID_to_BigQueryTableID_map_r5` (entityId, bq_table_id) VALUES ('syn26535445', 'isb-cgc-bq.HTAN.imaging_level4_OHSU_current'), ('syn53275842', 'isb-cgc-bq.HTAN.imaging_level4_OHSU_current'), ('syn53275838', 'isb-cgc-bq.HTAN.imaging_level4_OHSU_current'), ('syn26535453', 'isb-cgc-bq.HTAN.imaging_level4_OHSU_current'), ('syn31547329', 'isb-cgc-bq.HTAN.imaging_level4_OHSU_current');
-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.scRNAseq_VUMC_ABNORMALS_EPI_V2_r2`
(
  iObs INT64 OPTIONS(description="Index to cell barcodes."),
  iVar INT64 OPTIONS(description="Index to gene IDs."),
  X_value FLOAT64 OPTIONS(description="Expression value for a given gene and cell."),
  Cell_Barcode_Number STRING OPTIONS(description="Barcodes used for each droplet that contains the cell in the sequencing process"),
  HTAN_Parent_Data_File_ID STRING OPTIONS(description="HTAN Data File Identifier indicating the file(s) from which these files were derived"),
  HTAN_Biospecimen_ID STRING OPTIONS(description="HTAN ID associated with a biosample based on HTAN ID SOP (eg HTANx_yyy_zzz)"),
  Tissue_Subtype STRING OPTIONS(description="TA = tubular adenoma, HP = hyperplastic polyp, TVA = tubulovillus adenoma, SSL = sessile serrated lesion, MSI-H =microsatellite instability high CRC, MSS = microsatellite stable CRC"),
  Tissue_Type STRING OPTIONS(description="AD = conventional adenoma, SER = serrated polyp, MSI-H =microsatellite instability high CRC, MSS = microsatellite stable CRC"),
  Gene_Name STRING OPTIONS(description="Measured gene")
)
OPTIONS(
  friendly_name="HTAN HG38 SCRNASEQ GENE EXPRESSION CUMULATIVE ABNORMAL EPITHELIAL R2 VERSIONED",
  description="Data was derived in April 2022 from an H5AD file (Synapse ID: syn27056096) submitted by the Vanderbilt HTAN Center. This data set contains raw gene expression counts from 62 patient samples. Data was generated using the InDrop V2 chemistry (see https://doi.org/10.1186/s12864-020-06843-0 ) and was processed using a DropEst-based pipeline (see https://doi.org/10.1016/j.xpro.2021.100450 ), where reads were mapped to HG38, followed by processing with scanpy and aformentioned pipeline to filter cells. Low-dimensional embeddings are derived from a regulon space, generated using SCENIC. This dataset contains abnormal/tumor-specific epithelial cells derived from both the discovery (DIS) and validation (VAL) cohorts, as described in https://doi.org/10.1016/j.cell.2021.11.031.",
  labels=[("access", "open"), ("reference_genome", "hg38"), ("data_type", "gene_expression"), ("program", "htan"), ("source", "htan-vumc"), ("category", "processed_-omics_data"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.scRNAseq_VUMC_ABNORMALS_EPI_V2_r2` (iObs, iVar, X_value, Cell_Barcode_Number, HTAN_Parent_Data_File_ID, HTAN_Biospecimen_ID, Tissue_Subtype, Tissue_Type, Gene_Name) VALUES (18053, 24826, 9.0, 'GAGGACTTCCAGCGCGAT-2-5779-Polyp-2021', 'HTA11_9408_200000101113111', 'HTA11_9408_2000001011', 'TA', 'AD', 'RPS21'), (17094, 24751, 17.0, 'GTACCTTGAAACAGGG-0-5607-Polyp-2021', 'HTA11_10167_200000101113111', 'HTA11_10167_2000001011', 'SSL', 'SER', 'RPL14'), (8012, 14959, 9.0, 'TTCCGCTCGAGCGGTA-67', 'HTA11_2112_200000101113211', 'HTA11_2112_2000001011', 'HP', 'SER', 'NR3C2'), (19038, 24819, 29.0, 'TGAAACCCTTGTGTGCTCA-9-5779-Polyp-2021', 'HTA11_7663_200000101113211', 'HTA11_7663_2000001011', 'SSL', 'SER', 'RPS16'), (19479, 1835, 16.0, 'GACAAGAGGGGAGTTCAC-19-5779-Polyp-2021', 'HTA11_6801_200000102113111', 'HTA11_6801_2000001021', 'TA', 'AD', 'ALDOA');
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.census_bureau_usa.population_by_zip_2010`
(
  geo_id STRING OPTIONS(description="Geo code"),
  zipcode STRING NOT NULL OPTIONS(description="Five digit ZIP Code Tabulation Area Census Code"),
  population INT64 OPTIONS(description="The total count of the population for this segment."),
  minimum_age INT64 OPTIONS(description="The minimum age in the age range. If null, this indicates the row as a total for male, female, or overall population."),
  maximum_age INT64 OPTIONS(description="The maximum age in the age range. If null, this indicates the row as having no maximum (such as 85 and over) or the row is a total of the male, female, or overall population."),
  gender STRING OPTIONS(description="male or female. If empty, the row is a total population summary.")
)
OPTIONS(
  labels=[("freebqcovid", "")]
);

INSERT INTO `bigquery-public-data.census_bureau_usa.population_by_zip_2010` (geo_id, zipcode, population, minimum_age, maximum_age, gender) VALUES ('8600000US25647', '25647', 768, NULL, NULL, NULL), ('8600000US49336', '49336', 4352, NULL, NULL, NULL), ('8600000US72106', '72106', 5376, NULL, NULL, NULL), ('8600000US74074', '74074', 29184, NULL, NULL, NULL), ('8600000US01960', '1960', 50944, NULL, NULL, NULL);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.census_bureau_usa.population_by_zip_2000`
(
  zipcode STRING NOT NULL OPTIONS(description="Five digit ZIP Code Tabulation Area Census Code"),
  geo_id STRING OPTIONS(description="Geo code"),
  minimum_age INT64 OPTIONS(description="The minimum age in the age range. If null, this indicates the row as a total for male, female, or overall population."),
  maximum_age INT64 OPTIONS(description="The maximum age in the age range. If null, this indicates the row as having no maximum (such as 85 and over) or the row is a total of the male, female, or overall population."),
  gender STRING OPTIONS(description="male or female. If empty, the row is a total population summary."),
  population INT64 OPTIONS(description="The total count of the population for this segment.")
)
OPTIONS(
  labels=[("freebqcovid", "")]
);

INSERT INTO `bigquery-public-data.census_bureau_usa.population_by_zip_2000` (zipcode, geo_id, minimum_age, maximum_age, gender, population) VALUES ('62908', '8600000US62908', NULL, NULL, '', 512), ('50146', '8600000US50146', NULL, NULL, '', 512), ('25214', '8600000US25214', NULL, NULL, '', 768), ('58577', '8600000US58577', NULL, NULL, '', 1792), ('03447', '8600000US03447', NULL, NULL, '', 2048);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.utility_us.time`
(
  time TIME OPTIONS(description="Time as TIME - CAST('23:59:59' AS TIME)"),
  hour INT64 OPTIONS(description="Hour as INTEGER - [0, 23]"),
  minute INT64 OPTIONS(description="Minute as INTEGER - [0, 59]"),
  second INT64 OPTIONS(description="Second as INTEGER - [0, 59]"),
  second_in_day INT64 OPTIONS(description="Seconds as INTEGER - [0, 86399]; 00:00:00 = 0, 23:59:59 = 86399"),
  hour_ampm INT64 OPTIONS(description="Hour as INTEGER - [1, 12]"),
  is_pm BOOL OPTIONS(description="AM = False, PM = True")
);

INSERT INTO `bigquery-public-data.utility_us.time` (time, hour, minute, second, second_in_day, hour_ampm, is_pm) VALUES ('00:00:26', 0, 0, 26, 26, 12, False), ('00:00:35', 0, 0, 35, 35, 12, False), ('00:00:37', 0, 0, 37, 37, 12, False), ('00:00:46', 0, 0, 46, 46, 12, False), ('00:00:57', 0, 0, 57, 57, 12, False);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.utility_us.country_code_iso`
(
  country_name STRING NOT NULL OPTIONS(description=""),
  fips_code STRING OPTIONS(description=""),
  alpha_2_code STRING OPTIONS(description=""),
  alpha_3_code STRING OPTIONS(description=""),
  numeric_code STRING OPTIONS(description=""),
  stanag_code STRING OPTIONS(description=""),
  cctlds STRING OPTIONS(description=""),
  continent_code STRING OPTIONS(description=""),
  continent_name STRING OPTIONS(description="Note: Australia has been grouped into the Oceania region."),
  sub_continent_name STRING OPTIONS(description="")
);

INSERT INTO `bigquery-public-data.utility_us.country_code_iso` (country_name, fips_code, alpha_2_code, alpha_3_code, numeric_code, stanag_code, cctlds, continent_code, continent_name, sub_continent_name) VALUES ('Akrotiri', 'AX', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL), ('Bassas da India', 'BS', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL), ('Dhekelia', 'DX', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL), ('Europa Island', 'EU', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL), ('Glorioso Islands', 'GO', NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.associationByDatatypeIndirect`
(
  diseaseId STRING,
  targetId STRING,
  datatypeId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `open-targets-prod.platform.associationByDatatypeIndirect` (diseaseId, targetId, datatypeId, score, evidenceCount) VALUES ('EFO_0000677', 'ENSG00000187094', 'literature', 0.3846470249484239, 256), ('EFO_1000051', 'ENSG00000185499', 'literature', 0.7581854636368128, 256), ('EFO_0002422', 'ENSG00000147437', 'literature', 0.5861179253662822, 256), ('EFO_0000540', 'ENSG00000161955', 'literature', 0.9161655401042187, 256), ('MONDO_0000473', 'ENSG00000122194', 'literature', 0.5007441910332942, 256);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.go`
(
  id STRING,
  name STRING
);

INSERT INTO `open-targets-prod.platform.go` (id, name) VALUES ('GO:0030424', 'axon'), ('GO:0032059', 'bleb'), ('GO:0060417', 'yolk'), ('GO:0008623', 'CHRAC'), ('GO:0098986', 'T-bar');
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.diseaseToPhenotype`
(
  disease STRING,
  phenotype STRING,
  evidence STRUCT<list ARRAY<STRUCT<element STRUCT<aspect STRING, bioCuration STRING, diseaseFromSourceId STRING, diseaseFromSource STRING, diseaseName STRING, evidenceType STRING, frequency STRING, modifiers STRUCT<list ARRAY<STRUCT<element STRING>>>, onset STRUCT<list ARRAY<STRUCT<element STRING>>>, qualifier STRING, qualifierNot BOOL NOT NULL, references STRUCT<list ARRAY<STRUCT<element STRING>>>, sex STRING, resource STRING> NOT NULL>>> NOT NULL
);

INSERT INTO `open-targets-prod.platform.diseaseToPhenotype` (disease, phenotype, evidence) VALUES ('Orphanet_552', 'HP_0001520', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040283', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0004924', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040282', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0000831', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040283', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0000119', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040284', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"}), ('Orphanet_552', 'HP_0003076', {'list': "[{'element': {'aspect': 'P', 'bioCuration': 'ORPHA:orphadata[2024-04-24]', 'diseaseFromSourceId': 'ORPHA:552', 'diseaseFromSource': 'MODY', 'diseaseName': 'MODY', 'evidenceType': 'TAS', 'frequency': 'HP_0040282', 'modifiers': None, 'onset': None, 'qualifier': None, 'qualifierNot': False, 'references': {'list': array([{'element': 'ORPHA:552'}], dtype=object)}, 'sex': None, 'resource': 'HPO'}}]"});
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.associationByDatasourceDirect`
(
  datatypeId STRING,
  datasourceId STRING,
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64 NOT NULL
);

INSERT INTO `open-targets-prod.platform.associationByDatasourceDirect` (datatypeId, datasourceId, diseaseId, targetId, score, evidenceCount) VALUES ('genetic_association', 'eva', 'HP_0000023', 'ENSG00000049540', 0.19453785523571876, 1), ('genetic_association', 'eva', 'HP_0000062', 'ENSG00000184937', 0.547137717850459, 1), ('genetic_association', 'eva', 'HP_0000072', 'ENSG00000121075', 0.5592963338026914, 1), ('genetic_association', 'eva', 'HP_0000079', 'ENSG00000131778', 0.18237923928348632, 1), ('genetic_association', 'eva', 'HP_0000093', 'ENSG00000107611', 0.42555155832813474, 1);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.associationByOverallDirect`
(
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `open-targets-prod.platform.associationByOverallDirect` (diseaseId, targetId, score, evidenceCount) VALUES ('HP_0011123', 'ENSG00000112115', 0.03125583666870911, 256), ('EFO_0000544', 'ENSG00000170266', 0.017061128173156418, 256), ('EFO_0000616', 'ENSG00000104067', 0.10263100589238479, 256), ('EFO_0000616', 'ENSG00000062038', 0.12364904243044038, 256), ('EFO_0001063', 'ENSG00000150275', 0.6912231765727461, 256);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.associationByDatasourceIndirect`
(
  datatypeId STRING,
  datasourceId STRING,
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64 NOT NULL
);

INSERT INTO `open-targets-prod.platform.associationByDatasourceIndirect` (datatypeId, datasourceId, diseaseId, targetId, score, evidenceCount) VALUES ('genetic_association', 'eva', 'MONDO_0031052', 'ENSG00000109775', 0.7389736584301261, 3), ('genetic_association', 'eva', 'MONDO_0004736', 'ENSG00000178445', 0.9484126008765372, 2115), ('genetic_association', 'eva', 'MONDO_0002249', 'ENSG00000117400', 0.9415607406930349, 694), ('genetic_association', 'eva', 'MONDO_0004069', 'ENSG00000100416', 0.9163440231872357, 128), ('genetic_association', 'eva', 'HP_0011446', 'ENSG00000196628', 0.8150173921912369, 7);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.significantAdverseDrugReactions`
(
  chembl_id STRING,
  event STRING,
  count INT64 NOT NULL,
  llr FLOAT64,
  critval FLOAT64,
  meddraCode STRING
);

INSERT INTO `open-targets-prod.platform.significantAdverseDrugReactions` (chembl_id, event, count, llr, critval, meddraCode) VALUES ('CHEMBL2', 'hypotension', 53, 91.35776972666008, 6.251299745844193, '10021097'), ('CHEMBL3', 'jaundice neonatal', 43, 155.15858689508605, 38.961201902675384, '10023138'), ('CHEMBL3', 'macular degeneration', 114, 388.47462428933795, 38.961201902675384, '10025409'), ('CHEMBL3', 'drug abuse', 83, 86.02875766474244, 38.961201902675384, '10013654'), ('CHEMBL3', 'premature baby', 150, 299.56098443422525, 38.961201902675384, '10036590');
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.interaction`
(
  sourceDatabase STRING,
  targetA STRING,
  intA STRING,
  intABiologicalRole STRING,
  targetB STRING,
  intB STRING,
  intBBiologicalRole STRING,
  speciesA STRUCT<mnemonic STRING, scientific_name STRING, taxon_id INT64>,
  speciesB STRUCT<mnemonic STRING, scientific_name STRING, taxon_id INT64>,
  count INT64 NOT NULL,
  scoring FLOAT64
);

INSERT INTO `open-targets-prod.platform.interaction` (sourceDatabase, targetA, intA, intABiologicalRole, targetB, intB, intBBiologicalRole, speciesA, speciesB, count, scoring) VALUES ('intact', 'ENSG00000131738', 'Q14525', 'unspecified role', 'ENSG00000110046', 'A0AUL9', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000181085', 'Q8TD08', 'unspecified role', 'ENSG00000117868', 'A0FGR8', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000102098', 'Q9UQR0', 'unspecified role', 'ENSG00000278522', 'A0JP26', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000144746', 'O75915', 'unspecified role', 'ENSG00000110900', 'A1L157', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.35), ('intact', 'ENSG00000149177', 'Q12913-3', 'unspecified role', 'ENSG00000239887', 'A1L170', 'unspecified role', {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, {'mnemonic': 'human', 'scientific_name': 'Homo sapiens', 'taxon_id': 9606}, 1, 0.27);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.hpo`
(
  dbXRefs STRUCT<list ARRAY<STRUCT<element STRING>>>,
  description STRING,
  id STRING,
  name STRING,
  namespace STRUCT<list ARRAY<STRUCT<element STRING>>>,
  obsolete_terms STRUCT<list ARRAY<STRUCT<element STRING>>>,
  parents STRUCT<list ARRAY<STRUCT<element STRING>>>
);

INSERT INTO `open-targets-prod.platform.hpo` (dbXRefs, description, id, name, namespace, obsolete_terms, parents) VALUES (NULL, NULL, 'CL_1001567', 'lung endothelial cell', {'list': "[{'element': 'cl'}]"}, NULL, {'list': "[{'element': 'b43134'} {'element': 'CL_0000082'} {'element': 'CL_0002139'}]"}), ({'list': "[{'element': 'BTO:0001141'}]"}, NULL, 'CL_1001568', 'pulmonary artery endothelial cell', {'list': "[{'element': 'cl'}]"}, NULL, {'list': "[{'element': 'b44524'} {'element': 'CL_1000413'}]"}), (NULL, 'The various hormone- or neurotransmitter-secreting cells present throughout the mucosa of the intestinal tract.', 'CL_1001516', 'intestinal enteroendocrine cell', {'list': "[{'element': 'cl'}]"}, NULL, {'list': "[{'element': 'CL_0002563'} {'element': 'CL_0000164'}]"}), (NULL, NULL, 'BFO_0000019', 'quality', {'list': "[{'element': 'bfo'}]"}, NULL, {'list': "[{'element': 'b24511'} {'element': 'BFO_0000020'}]"}), (NULL, 'An independent continuant that is spatially extended whose identity is independent of that of other entities and can be maintained through time.', 'BFO_0000040', 'material entity', {'list': "[{'element': 'bfo'}]"}, NULL, {'list': "[{'element': 'BFO_0000004'}]"});
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.indication`
(
  id STRING,
  indications STRUCT<list ARRAY<STRUCT<element STRUCT<disease STRING, efoName STRING, references STRUCT<list ARRAY<STRUCT<element STRUCT<source STRING, ids STRUCT<list ARRAY<STRUCT<element STRING>>> NOT NULL> NOT NULL>>> NOT NULL, maxPhaseForIndication FLOAT64> NOT NULL>>> NOT NULL,
  approvedIndications STRUCT<list ARRAY<STRUCT<element STRING NOT NULL>>> NOT NULL,
  indicationCount INT64 NOT NULL
);

INSERT INTO `open-targets-prod.platform.indication` (id, indications, approvedIndications, indicationCount) VALUES ('CHEMBL500826', {'list': "[{'element': {'disease': 'EFO_1001888', 'efoName': 'eye infection', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'S01AX10'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                             ]"}, {'list': '[]'}, 1), ('CHEMBL3989504', {'list': "[{'element': {'disease': 'EFO_0000771', 'efoName': 'bacterial disease', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'J01MA21'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                                 ]"}, {'list': '[]'}, 1), ('CHEMBL36633', {'list': "[{'element': {'disease': 'EFO_0003888', 'efoName': 'attention deficit hyperactivity disorder', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'N06BX07'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                                                        ]"}, {'list': '[]'}, 1), ('CHEMBL3989705', {'list': "[{'element': {'disease': 'EFO_1001888', 'efoName': 'eye infection', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'S01AX10'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                             ]"}, {'list': '[]'}, 1), ('CHEMBL3989444', {'list': "[{'element': {'disease': 'EFO_0000319', 'efoName': 'cardiovascular disease', 'references': {'list': array([{'element': {'source': 'ATC', 'ids': {'list': array([{'element': 'C04AX24'}], dtype=object)}}}],\n       dtype=object)}, 'maxPhaseForIndication': 2.0}}                                                                                                                                                      ]"}, {'list': '[]'}, 1);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.associationByDatatypeDirect`
(
  diseaseId STRING,
  targetId STRING,
  datatypeId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `open-targets-prod.platform.associationByDatatypeDirect` (diseaseId, targetId, datatypeId, score, evidenceCount) VALUES ('EFO_0000182', 'ENSG00000157404', 'known_drug', 0.9776027328690036, 256), ('EFO_0000222', 'ENSG00000130816', 'literature', 0.9317724820898985, 256), ('EFO_0000544', 'ENSG00000170266', 'literature', 0.14032130170230317, 256), ('EFO_0000616', 'ENSG00000104067', 'literature', 0.8441010580117951, 256), ('MONDO_0004992', 'ENSG00000162434', 'literature', 0.6289120158371304, 256);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.drugWarnings`
(
  chemblIds STRUCT<list ARRAY<STRUCT<element STRING>>>,
  toxicityClass STRING,
  country STRING,
  description STRING,
  id INT64,
  references STRUCT<list ARRAY<STRUCT<element STRUCT<ref_id STRING, ref_type STRING, ref_url STRING>>>>,
  warningType STRING,
  year INT64,
  efo_term STRING,
  efo_id STRING,
  efo_id_for_warning_class STRING
);

INSERT INTO `open-targets-prod.platform.drugWarnings` (chemblIds, toxicityClass, country, description, id, references, warningType, year, efo_term, efo_id, efo_id_for_warning_class) VALUES ({'list': "[{'element': 'CHEMBL3039594'} {'element': 'CHEMBL3039597'}]"}, NULL, 'United States', NULL, 2817, {'list': '[]'}, 'Black Box Warning', NULL, NULL, NULL, NULL), ({'list': "[{'element': 'CHEMBL3989677'} {'element': 'CHEMBL1457'}]"}, NULL, 'United States', NULL, 2818, {'list': '[]'}, 'Black Box Warning', NULL, NULL, NULL, NULL), ({'list': "[{'element': 'CHEMBL2359966'} {'element': 'CHEMBL170'}]"}, NULL, 'United States', NULL, 2820, {'list': '[]'}, 'Black Box Warning', NULL, NULL, NULL, NULL), ({'list': "[{'element': 'CHEMBL5095051'} {'element': 'CHEMBL637'}]"}, NULL, 'United States', NULL, 2864, {'list': '[]'}, 'Black Box Warning', NULL, NULL, NULL, NULL), ({'list': "[{'element': 'CHEMBL1742992'}]"}, NULL, 'United States', NULL, 221, {'list': '[]'}, 'Black Box Warning', NULL, NULL, NULL, NULL);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.associationByOverallIndirect`
(
  diseaseId STRING,
  targetId STRING,
  score FLOAT64,
  evidenceCount INT64
);

INSERT INTO `open-targets-prod.platform.associationByOverallIndirect` (diseaseId, targetId, score, evidenceCount) VALUES ('HP_0000818', 'ENSG00000104763', 0.01986139901938229, 256), ('EFO_0000319', 'ENSG00000173511', 0.5365813595209584, 256), ('EFO_0000519', 'ENSG00000138798', 0.31838517223016705, 256), ('EFO_0000616', 'ENSG00000114770', 0.13776394783236456, 256), ('EFO_0000684', 'ENSG00000101017', 0.13249235774111517, 256);
-- DBMS: bigquery
CREATE TABLE `open-targets-prod.platform.targetPrioritisation`
(
  targetId STRING,
  isInMembrane INT64,
  isSecreted INT64,
  hasSafetyEvent INT64,
  hasPocket INT64,
  hasLigand INT64,
  hasSmallMoleculeBinder INT64,
  geneticConstraint FLOAT64,
  paralogMaxIdentityPercentage FLOAT64,
  mouseOrthologMaxIdentityPercentage FLOAT64,
  isCancerDriverGene INT64,
  hasTEP INT64,
  mouseKOScore FLOAT64,
  hasHighQualityChemicalProbes INT64,
  maxClinicalTrialPhase FLOAT64,
  tissueSpecificity FLOAT64,
  tissueDistribution FLOAT64
);

INSERT INTO `open-targets-prod.platform.targetPrioritisation` (targetId, isInMembrane, isSecreted, hasSafetyEvent, hasPocket, hasLigand, hasSmallMoleculeBinder, geneticConstraint, paralogMaxIdentityPercentage, mouseOrthologMaxIdentityPercentage, isCancerDriverGene, hasTEP, mouseKOScore, hasHighQualityChemicalProbes, maxClinicalTrialPhase, tissueSpecificity, tissueDistribution) VALUES ('ENSG00000234859', NULL, NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, nan, NULL, nan, nan, nan), ('ENSG00000293334', NULL, NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, nan, NULL, nan, nan, nan), ('ENSG00000200774', NULL, NULL, NULL, NULL, NULL, NULL, nan, -0.5909099999999998, nan, NULL, NULL, nan, NULL, nan, nan, nan), ('ENSG00000233593', NULL, NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, nan, NULL, nan, nan, nan), ('ENSG00000235408', NULL, NULL, NULL, NULL, NULL, NULL, nan, nan, nan, NULL, NULL, nan, NULL, nan, nan, nan);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.post_links`
(
  id INT64,
  creation_date TIMESTAMP,
  link_type_id INT64,
  post_id INT64,
  related_post_id INT64
);

INSERT INTO `bigquery-public-data.stackoverflow.post_links` (id, creation_date, link_type_id, post_id, related_post_id) VALUES (1894, '2010-04-26 03:00:57.193000+00:00', 1, 131759, 192892), (1925, '2010-04-26 03:00:57.613000+00:00', 1, 133236, 769338), (1926, '2010-04-26 03:00:57.647000+00:00', 1, 133335, 122533), (2196, '2010-04-26 03:01:00.657000+00:00', 1, 145271, 111161), (2560, '2010-04-26 03:01:05.790000+00:00', 1, 160298, 773);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.comments`
(
  id INT64,
  text STRING,
  creation_date TIMESTAMP,
  post_id INT64,
  user_id INT64,
  user_display_name STRING,
  score INT64
);

INSERT INTO `bigquery-public-data.stackoverflow.comments` (id, text, creation_date, post_id, user_id, user_display_name, score) VALUES (32669925, 'What is there to say?  In array context, as provided by `my @fileData`, the `<>` operator reads lines into the array with an implicit loop.  It works.  Occasionally, it is useful. Perl has a couple of mottos.  One is TMTOWTDI — There''s More Than One Way To Do It.  Another is DWIM — Do What I Mean; at least, Perl does this more than many languages, provided you know what you''re asking for.  This is a piece of dwimmery.', '2014-02-07 06:35:37.693000+00:00', 21620857, 15168, NULL, 5), (32670020, '... and it takes 2 seconds to add it to windows (8.1 in my case) > Control Panel > Add Programes > Turn windows features on', '2014-02-07 06:39:30.367000+00:00', 8920568, 81053, NULL, 30), (32670048, 'Yes, the 4th argument being "0" causes the replaecment string to be inserted without overwriting any of the original string.', '2014-02-07 06:40:59.910000+00:00', 17880260, 631764, NULL, 14), (32670086, 'See here https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Member_Operators', '2014-02-07 06:42:53.817000+00:00', 21620988, 670396, NULL, 5), (32670116, 'The question didn''t ask for encryption and decryption. It only asked for key pair generation. And encryption and decryption is very well explained in documentation.', '2014-02-07 06:44:10.983000+00:00', 20877180, 1468663, NULL, 24);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.posts_tag_wiki_excerpt`
(
  id INT64,
  title STRING,
  body STRING,
  accepted_answer_id STRING,
  answer_count STRING,
  comment_count INT64,
  community_owned_date TIMESTAMP,
  creation_date TIMESTAMP,
  favorite_count STRING,
  last_activity_date TIMESTAMP,
  last_edit_date TIMESTAMP,
  last_editor_display_name STRING,
  last_editor_user_id INT64,
  owner_display_name STRING,
  owner_user_id INT64,
  parent_id STRING,
  post_type_id INT64,
  score INT64,
  tags STRING,
  view_count STRING
);

INSERT INTO `bigquery-public-data.stackoverflow.posts_tag_wiki_excerpt` (id, title, body, accepted_answer_id, answer_count, comment_count, community_owned_date, creation_date, favorite_count, last_activity_date, last_edit_date, last_editor_display_name, last_editor_user_id, owner_display_name, owner_user_id, parent_id, post_type_id, score, tags, view_count) VALUES (4742863, NULL, 'SlimDX is an MIT-licensed, open-source framework that allows developers working with managed languages like C# and IronPython to leverage DirectX and many of Microsoft''s other gaming-related multimedia APIs.', NULL, NULL, 0, 'NaT', '2011-01-20 02:14:32.800000+00:00', NULL, '2011-01-20 02:14:32.800000+00:00', '2011-01-20 02:14:32.800000+00:00', 'user197015', NULL, 'user197015', NULL, NULL, 4, 0, NULL, NULL), (5062416, NULL, 'Celerity is a JRuby wrapper around HtmlUnit – a headless Java browser with JavaScript support. It provides a simple API for programmatic navigation through web applications. Celerity aims at being API compatible with Watir.', NULL, NULL, 0, 'NaT', '2011-02-21 04:49:10.940000+00:00', NULL, '2011-02-21 04:54:07.800000+00:00', '2011-02-21 04:54:07.800000+00:00', 'user479911', NULL, 'user479911', NULL, NULL, 4, 0, NULL, NULL), (5130475, NULL, 'Ramaze is a simple, light and modular open-source web application framework written in Ruby.', NULL, NULL, 0, 'NaT', '2011-02-26 23:38:37.057000+00:00', NULL, '2011-02-27 00:08:46.880000+00:00', '2011-02-27 00:08:46.880000+00:00', 'user290102', NULL, 'user290102', NULL, NULL, 4, 0, NULL, NULL), (5304008, NULL, 'WebMachine is an Erlang framework for creating RESTful Web Services using Erlang/OTP best practices.', NULL, NULL, 0, 'NaT', '2011-03-14 20:20:45.170000+00:00', NULL, '2011-03-14 20:44:11.377000+00:00', '2011-03-14 20:44:11.377000+00:00', 'user177800', NULL, 'user177800', NULL, NULL, 4, 0, NULL, NULL), (5354120, NULL, 'TCP/IP (Transmission Control Protocol/Internet Protocol) is the basic communication language or protocol of the Internet. It can also be used as a communications protocol in a private network (either an intranet or an extranet).', NULL, NULL, 0, 'NaT', '2011-03-18 15:24:37.813000+00:00', NULL, '2011-03-18 15:27:51.537000+00:00', '2011-03-18 15:27:51.537000+00:00', 'user614868', NULL, 'user614868', NULL, NULL, 4, 0, NULL, NULL);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.users`
(
  id INT64,
  display_name STRING,
  about_me STRING,
  age STRING,
  creation_date TIMESTAMP,
  last_access_date TIMESTAMP,
  location STRING,
  reputation INT64,
  up_votes INT64,
  down_votes INT64,
  views INT64,
  profile_image_url STRING,
  website_url STRING
);

INSERT INTO `bigquery-public-data.stackoverflow.users` (id, display_name, about_me, age, creation_date, last_access_date, location, reputation, up_votes, down_votes, views, profile_image_url, website_url) VALUES (282, 'Bert Lamb', '<p>Director of Engineering, Litmus.com</p>', NULL, '2008-08-04 12:18:45.500000+00:00', '2022-02-07 15:14:57.867000+00:00', 'Durham, NH, USA', 2265, 141, 2, 195, NULL, 'http://www.bertlamb.com'), (2832, 'Thunder3', NULL, NULL, '2008-08-25 12:57:37.340000+00:00', '2012-04-12 15:38:12.890000+00:00', 'California', 1108, 14, 1, 118, NULL, NULL), (6209, 'Micah', NULL, NULL, '2008-09-12 23:03:24.723000+00:00', '2021-09-15 14:37:48.553000+00:00', NULL, 1507, 35, 0, 83, NULL, NULL), (7706, 'indentation', NULL, NULL, '2008-09-15 14:16:37.957000+00:00', '2008-10-16 18:51:07.430000+00:00', NULL, 9727, 0, 0, 102, NULL, NULL), (11791, 'cbcolin', NULL, NULL, '2008-09-16 11:15:51.800000+00:00', '2011-04-29 15:44:21.927000+00:00', NULL, 371, 0, 0, 52, NULL, NULL);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.votes`
(
  id INT64,
  creation_date TIMESTAMP,
  post_id INT64,
  vote_type_id INT64
);

INSERT INTO `bigquery-public-data.stackoverflow.votes` (id, creation_date, post_id, vote_type_id) VALUES (246000083, '2022-01-31 00:00:00+00:00', 70928934, 15), (246062313, '2022-02-01 00:00:00+00:00', 70942438, 11), (239397522, '2021-09-29 00:00:00+00:00', 69374423, 11), (239441896, '2021-09-30 00:00:00+00:00', 69375289, 15), (135787328, '2017-04-01 00:00:00+00:00', 43161698, 11);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.tags`
(
  id INT64,
  tag_name STRING,
  count INT64,
  excerpt_post_id INT64,
  wiki_post_id INT64
);

INSERT INTO `bigquery-public-data.stackoverflow.tags` (id, tag_name, count, excerpt_post_id, wiki_post_id) VALUES (149358, 'announcement', 0, 69362460, 69362459), (2136, 'regsvr32', 256, 10051236, 10051235), (8287, 'rpg', 256, 7080550, 7080549), (9136, 'dbexpress', 256, 7663373, 7663372), (9213, 'multiple-domains', 256, 22931444, 22931443);
-- DBMS: bigquery
CREATE TABLE `bigquery-public-data.stackoverflow.badges`
(
  id INT64,
  name STRING,
  date TIMESTAMP,
  user_id INT64,
  class INT64,
  tag_based BOOL
);

INSERT INTO `bigquery-public-data.stackoverflow.badges` (id, name, date, user_id, class, tag_based) VALUES (286426, 'Great Answer', '2009-04-17 07:22:38.120000+00:00', 49786, 1, False), (1096086, 'Unsung Hero', '2010-10-01 01:10:23.593000+00:00', 164998, 1, False), (1237100, 'Great Question', '2010-11-27 21:45:43.777000+00:00', 86060, 1, False), (1352523, 'Great Answer', '2011-01-16 05:33:11.323000+00:00', 16076, 1, False), (1364351, 'Stellar Question', '2011-01-20 11:45:12.737000+00:00', 1043, 1, False);
-- DBMS: bigquery
CREATE TABLE `fh-bigquery.hackernews.comments`
(
  id INT64,
  `by` STRING,
  author STRING,
  time INT64,
  time_ts TIMESTAMP,
  text STRING,
  parent INT64,
  deleted BOOL,
  dead BOOL,
  ranking INT64
)
OPTIONS(
  description="abandoned, use https://bigquery.cloud.google.com/table/bigquery-public-data:hacker_news.full?tab=details instead"
);

INSERT INTO `fh-bigquery.hackernews.comments` (id, by, author, time, time_ts, text, parent, deleted, dead, ranking) VALUES (5955678, NULL, NULL, 1372382003, '2013-06-28 01:13:23+00:00', NULL, 5955670, True, NULL, 0), (9325450, NULL, NULL, 1428270522, '2015-04-05 21:48:42+00:00', NULL, 9325417, True, NULL, 0), (8752122, NULL, NULL, 1418654125, '2014-12-15 14:35:25+00:00', NULL, 8751894, True, NULL, 0), (1132360, NULL, NULL, 1266436359, '2010-02-17 19:52:39+00:00', NULL, 1132327, True, NULL, 0), (7259942, NULL, NULL, 1392748029, '2014-02-18 18:27:09+00:00', NULL, 7259214, True, NULL, 0);