Included JSON single value text field use case (#92)

* Include bin info (commit hash and if changed) on tool

* Include tag large scale

* Included JSON single value text field use case

scripts/datagen_redisearch/json_single_text/__init__.py

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+import sys
+import os
+
+sys.path.append(os.getcwd() + "/..")

scripts/datagen_redisearch/json_single_text/ftsb_generate_json_singlevalue_numeric.py

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+#!/usr/bin/python3
+
+import argparse
+import csv
+import json
+import os
+import random
+
+# package local imports
+import sys
+import uuid
+
+import boto3
+from tqdm import tqdm
+
+sys.path.append(os.getcwd() + "/..")
+
+from common_datagen import (
+    download_url,
+    generate_setup_json,
+    compress_files,
+    generate_inputs_dict_item,
+    humanized_bytes,
+    del_non_use_case_specific_keys,
+    add_key_metric,
+    upload_dataset_artifacts_s3,
+    add_deployment_requirements_redis_server_module,
+    add_deployment_requirements_benchmark_tool,
+    add_deployment_requirements_utilities,
+    init_deployment_requirement,
+    remove_file_if_exists,
+)
+from pathlib import Path
+import string
+
+
+def str_to_float_or_zero(entry):
+    val = 0.0
+    try:
+        val = float(entry)
+    except ValueError as e:
+        pass
+    return val
+
+
+def index_or_none(list, value):
+    index = None
+    try:
+        index = list.index(value)
+    except ValueError:
+        pass
+    return index
+
+
+def rand_str(minN, maxN):
+    return "".join(
+        random.choices(
+            string.ascii_uppercase + string.digits, k=random.randint(minN, maxN)
+        )
+    )
+
+
+def rand_arr(minN, maxN):
+    arr = []
+    for x in range(1, random.randint(minN, maxN)):
+        arr.append(rand_str(3, 10))
+    return arr
+
+
+def rand_numeric_arr(minN, maxN):
+    arr = []
+    for x in range(1, random.randint(minN, maxN)):
+        arr.append(get_rand_int_v())
+    return arr
+
+
+def get_rand_int_v(start_val=-1000, end_val=1000):
+    return random.randint(start_val, end_val)
+
+
+def get_rand_float_v(start_val=-1000.0, end_val=1000.0):
+    return random.random() * (end_val - start_val) + start_val
+
+
+def rand_numeric_float_arr(minN, maxN):
+    arr = []
+    for x in range(1, random.randint(minN, maxN)):
+        arr.append(get_rand_float_v())
+    return arr
+
+
+def use_case_csv_row_to_cmd(doc_id):
+    numeric_int = rand_numeric_arr(1, 10)
+    numeric_float = rand_numeric_float_arr(1, 10)
+    doc = {}
+    # for n, v in enumerate(numeric_int):
+    #     doc["numericInt{}".format(n + 1)] = v
+    # for n, v in enumerate(numeric_float):
+    #     doc["numericFloat{}".format(n + 1)] = v
+    doc["field1"]= rand_str(10,20)
+    docid_str = "doc:single:{hash}:{n}".format(hash=uuid.uuid4().hex, n=doc_id)
+
+    cmd = ["WRITE", "W1", 1, "JSON.SET", docid_str, ".", "{}".format(json.dumps(doc))]
+    return docid_str, cmd
+
+
+def human_format(num):
+    magnitude = 0
+    while abs(num) >= 1000:
+        magnitude += 1
+        num /= 1000.0
+    # add more suffixes if you need them
+    return "%.0f%s" % (num, ["", "K", "M", "G", "T", "P"][magnitude])
+
+
+def ft_search_numeric_int(index_name):
+    val_from = get_rand_int_v(-1000, 500)
+    val_to = get_rand_int_v(val_from + 1)
+    condition = "'@numericInt1:[{} {}]".format(val_from, val_to)
+    for n in range(2, 11):
+        condition = condition + "|@numericInt{}:[{} {}]".format(n, val_from, val_to)
+    condition = condition + "'"
+    return ["READ", "R1", 1, "FT.SEARCH", index_name, condition, "NOCONTENT"]
+
+
+def ft_search_numeric_float(index_name):
+    val_from = get_rand_float_v(-1000.0, 500.0)
+    val_to = get_rand_float_v(val_from + 1.0)
+    condition = "'@numericFloat1:[{} {}]".format(val_from, val_to)
+    for n in range(2, 11):
+        condition = condition + "|@numericFloat{}:[{} {}]".format(n, val_from, val_to)
+    condition = condition + "'"
+    return ["READ", "R2", 1, "FT.SEARCH", index_name, condition, "NOCONTENT"]
+
+
+SEARCH_NUMERIC_FLOAT = "FT.SEARCH-SINGLEVALUE-FLOAT"
+SEARCH_NUMERIC_INT = "FT.SEARCH-SINGLEVALUE-INT"
+""
+choices_str = ",".join([SEARCH_NUMERIC_FLOAT, SEARCH_NUMERIC_INT])
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="RediSearch FTSB data generator.",
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument(
+        "--project", type=str, default="redisjson", help="the project being tested"
+    )
+    parser.add_argument(
+        "--index-name",
+        type=str,
+        default="idx:single",
+        help="the index name used for search commands",
+    )
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=12345,
+        help="the random seed used to generate random deterministic outputs",
+    )
+    parser.add_argument(
+        "--query-choices",
+        type=str,
+        default=choices_str,
+        help="comma separated list of queries to produce. one of: {}".format(
+            choices_str
+        ),
+    )
+    parser.add_argument(
+        "--doc-limit",
+        type=int,
+        default=10000000,
+        help="the total documents to generate to be added in the setup stage",
+    )
+    parser.add_argument(
+        "--total-benchmark-commands",
+        type=int,
+        default=1000000,
+        help="the total commands to generate to be issued in the benchmark stage",
+    )
+    parser.add_argument(
+        "--test-name",
+        type=str,
+        default="singlevalue-text-json",
+        help="the name of the test",
+    )
+    parser.add_argument(
+        "--test-description",
+        type=str,
+        default="benchmark making usage of POST format as the dump of StackOverflow posts.",
+        help="the full description of the test",
+    )
+    parser.add_argument(
+        "--upload-artifacts-s3",
+        default=False,
+        action="store_true",
+        help="uploads the generated dataset files and configuration file to public benchmarks.redislabs bucket. Proper credentials are required",
+    )
+    parser.add_argument(
+        "--upload-artifacts-s3-uncompressed",
+        action="store_true",
+        help="uploads the generated dataset files and configuration file to public benchmarks.redislabs bucket. Proper credentials are required",
+    )
+    parser.add_argument(
+        "--temporary-work-dir",
+        type=str,
+        default="./tmp",
+        help="The temporary dir to use as working directory for file download, compression,etc... ",
+    )
+
+    args = parser.parse_args()
+    use_case_specific_arguments = del_non_use_case_specific_keys(dict(args.__dict__))
+    query_choices = args.query_choices.split(",")
+    total_benchmark_commands = args.total_benchmark_commands
+    # generate the temporary working dir if required
+    working_dir = args.temporary_work_dir
+    Path(working_dir).mkdir(parents=True, exist_ok=True)
+    seed = args.seed
+    project = args.project
+    doc_limit = args.doc_limit
+    test_name = args.test_name
+    index_name = args.index_name
+    description = args.test_description
+    test_name = "{}-{}".format(human_format(doc_limit), test_name)
+    s3_bucket_name = "benchmarks.redislabs"
+    s3_bucket_path = "redisearch/datasets/{}/".format(test_name)
+    s3_uri = "https://s3.amazonaws.com/{bucket_name}/{bucket_path}".format(
+        bucket_name=s3_bucket_name, bucket_path=s3_bucket_path
+    )
+
+    benchmark_output_file = "{test_name}.{project}.commands".format(
+        test_name=test_name, project=project
+    )
+    benchmark_config_file = "{test_name}.{project}.cfg.json".format(
+        test_name=test_name, project=project
+    )
+    bench_fname = "{}.BENCH.csv".format(benchmark_output_file, "__".join(query_choices))
+    setup_fname = "{}.SETUP.csv".format(benchmark_output_file)
+
+    ## remove previous files if they exist
+    remove_file_if_exists(benchmark_config_file)
+    remove_file_if_exists(bench_fname)
+    remove_file_if_exists(setup_fname)
+
+    used_indices = []
+    setup_commands = []
+    teardown_commands = []
+    key_metrics = []
+
+    total_writes = 0
+    total_reads = 0
+    total_updates = 0
+    total_deletes = 0
+
+    json_version = "0.1"
+    benchmark_repetitions_require_teardown_and_resetup = True
+
+    print("-- Benchmark: {} -- ".format(test_name))
+    print("-- Description: {} -- ".format(description))
+
+    total_docs = 0
+
+    print("Using random seed {0}".format(args.seed))
+    random.seed(args.seed)
+
+    total_docs = 0
+    doc_ids = []
+
+    progress = tqdm(unit="docs", total=doc_limit)
+    all_csvfile = open(setup_fname, "a", newline="")
+    all_csv_writer = csv.writer(all_csvfile, delimiter=",")
+    for row_n in range(0, doc_limit):
+        docid, cmd = use_case_csv_row_to_cmd(row_n)
+        all_csv_writer.writerow(cmd)
+        progress.update()
+        doc_ids.append(docid)
+    progress.close()
+    all_csvfile.close()
+    # progress = tqdm(unit="docs", total=total_benchmark_commands)
+    # all_csvfile = open(bench_fname, "a", newline="")
+    # all_csv_writer = csv.writer(all_csvfile, delimiter=",")
+    # len_docs = len(doc_ids)
+    # row_n = 0
+    # while row_n < total_benchmark_commands:
+    #     doc_id = doc_ids[random.randint(0, len_docs - 1)]
+    #     choice = random.choices(query_choices)[0]
+    #     if choice == SEARCH_NUMERIC_INT:
+    #         cmd = ft_search_numeric_int(index_name)
+    #     elif choice == SEARCH_NUMERIC_FLOAT:
+    #         cmd = ft_search_numeric_float(index_name)
+    #     row_n = row_n + 1
+    #     all_csv_writer.writerow(cmd)
+    #     progress.update()
+    # progress.close()
+    # all_csvfile.close()
+
+    if args.upload_artifacts_s3:
+        artifacts = [setup_fname]
+        upload_dataset_artifacts_s3(s3_bucket_name, s3_bucket_path, artifacts)
+
+    print("############################################")
+    print("All artifacts generated.")
+
+    create_cmd = "FT.CREATE {} ON JSON PREFIX 1 doc:single SCHEMA".format(index_name)
+    for n in range(1, 11):
+        create_cmd = create_cmd + " $.numericInt{} AS numericInt{} NUMERIC".format(n, n)
+        create_cmd = create_cmd + " $.numericFloat{} AS numericFloat{} NUMERIC".format(
+            n, n
+        )
+    print("FT.CREATE command:{}".format(create_cmd))

scripts/datagen_redisearch/tag_large_scale/__init__.py

@@ -0,0 +1,4 @@
+import sys
+import os
+
+sys.path.append(os.getcwd() + "/..")