def test_offset_upgrade(sdc_builder, sdc_executor, elasticsearch):
"""Ensure that when upgrading from older offset format (that can be generated by either SCH or by upgrading
pre-multithreaded pipeline) we properly upgrade the offset and the pipeline will not re-read everything
from the source.
"""
es_index = get_random_string(string.ascii_letters, 10).lower()
es_doc_id = get_random_string(string.ascii_letters, 10)
raw_str = 'Hello World!'
builder = sdc_builder.get_pipeline_builder()
es_origin = builder.add_stage('Elasticsearch', type='origin')
es_origin.set_attributes(index=es_index,
query="{'query': {'match_all': {}}}")
trash = builder.add_stage('Trash')
es_origin >> trash
pipeline = builder.build().configure_for_environment(elasticsearch)
sdc_executor.add_pipeline(pipeline)
# We hard code offset to be pre-migration to multi-threaded origin and thus forcing the origin to upgrade it
offset = {
'offsets': {
'$com.streamsets.datacollector.pollsource.offset$': None,
},
'version': 2
}
sdc_executor.api_client.update_pipeline_committed_offsets(pipeline.id,
body=offset)
try:
# Put data to Elasticsearch
elasticsearch.connect()
doc_type = DocType(meta={'id': es_doc_id, 'index': es_index})
doc_type.body = raw_str
doc_type.save() # save document to Elasticsearch
index = Index(es_index)
assert index.refresh(
) # assert to refresh index, making all operations available for search
# Run pipeline and assert
snapshot = sdc_executor.capture_snapshot(pipeline,
start_pipeline=True).snapshot
# no need to stop pipeline - as ES origin shuts off once data is read from Elasticsearch
snapshot_data = snapshot[es_origin.instance_name].output[0].field
# assert ES meta
assert snapshot_data['_index'] == es_index and snapshot_data[
'_id'] == es_doc_id
# assert ES data
assert snapshot_data['_source']['body'] == raw_str
# Now let's validate that the offset doesn't have the poll key any more
offset = sdc_executor.api_client.get_pipeline_committed_offsets(
pipeline.id).response.json()
assert offset is not None
assert '$com.streamsets.datacollector.pollsource.offset$' not in offset[
'offsets']
finally:
# Clean up test data in ES
idx = Index(es_index)
idx.delete()
def test_elasticsearch_pipeline_errors(sdc_builder, sdc_executor,
elasticsearch):
"""Test for a pipeline's error records being pumped to Elasticsearch. We do so by making a Dev Raw Data source
target to Error stage which would send records to the pipeline configured Elasticsearch error records handling.
We then assert the error records what we find in Elasticsearch. The pipeline would look like:
Elasticsearch error pipeline:
dev_raw_data_source >> error_target
"""
# Test static
es_index = get_random_string(
string.ascii_letters,
10).lower() # Elasticsearch indexes must be lower case
es_mapping = get_random_string(string.ascii_letters, 10)
es_doc_id = get_random_string(string.ascii_letters, 10)
raw_str = 'Hello World!'
# Build pipeline
builder = sdc_builder.get_pipeline_builder()
errstg = builder.add_error_stage('Write to Elasticsearch')
errstg.set_attributes(document_id=es_doc_id,
index=es_index,
mapping=es_mapping)
dev_raw_data_source = builder.add_stage(
'Dev Raw Data Source').set_attributes(data_format='TEXT',
stop_after_first_batch=True,
raw_data=raw_str)
error_target = builder.add_stage('To Error')
dev_raw_data_source >> error_target
es_error_pipeline = builder.build(
title='ES error pipeline').configure_for_environment(elasticsearch)
sdc_executor.add_pipeline(es_error_pipeline)
try:
elasticsearch.connect()
# Make sure that the index exists properly before running the test
index = Index(es_index)
index.create()
assert index.refresh()
# Run pipeline and read from Elasticsearch to assert
sdc_executor.start_pipeline(es_error_pipeline).wait_for_finished()
# Since we are upsert on the same index, map, doc - there should only be one document (index 0)
es_search = ESSearch(index=es_index)
es_response = _es_search_with_retry(es_search)
es_meta = es_response[0].meta
# assert meta ingest
assert es_meta['index'] == es_index and es_meta[
'doc_type'] == es_mapping and es_meta['id'] == es_doc_id
# assert data ingest
assert raw_str == es_response[0].text
finally:
# Clean up test data in ES
idx = Index(es_index)
idx.delete()
def test_elasticsearch_target(sdc_builder, sdc_executor, elasticsearch,
additional_properties):
"""Test for Elasticsearch target stage. We do so by ingesting data via Dev Raw Data source to
Elasticsearch stage and then asserting what we ingest to what will be read from Elasticsearch.
The pipeline looks like:
Elasticsearch target pipeline:
dev_raw_data_source >> es_target
"""
# Test static
es_index = get_random_string(
string.ascii_letters,
10).lower() # Elasticsearch indexes must be lower case
es_mapping = get_random_string(string.ascii_letters, 10)
es_doc_id = get_random_string(string.ascii_letters, 10)
raw_str = 'Hello World!'
# Build pipeline
builder = sdc_builder.get_pipeline_builder()
dev_raw_data_source = builder.add_stage(
'Dev Raw Data Source').set_attributes(data_format='TEXT',
raw_data=raw_str)
es_target = builder.add_stage('Elasticsearch', type='destination')
es_target.set_attributes(default_operation='INDEX',
document_id=es_doc_id,
index=es_index,
mapping=es_mapping,
additional_properties=additional_properties)
dev_raw_data_source >> es_target
es_target_pipeline = builder.build(
title='ES target pipeline').configure_for_environment(elasticsearch)
es_target_pipeline.configuration["shouldRetry"] = False
sdc_executor.add_pipeline(es_target_pipeline)
try:
# Run pipeline and read from Elasticsearch to assert
sdc_executor.start_pipeline(
es_target_pipeline).wait_for_pipeline_batch_count(1)
sdc_executor.stop_pipeline(es_target_pipeline)
# Since we are upsert on the same index, map, doc - there should only be one document (index 0)
elasticsearch.connect()
es_search = ESSearch(index=es_index)
es_response = es_search.execute()
es_meta = es_response[0].meta
# assert meta ingest
assert es_meta['index'] == es_index and es_meta[
'doc_type'] == es_mapping and es_meta['id'] == es_doc_id
# assert data ingest
assert raw_str == es_response[0].text
finally:
# Clean up test data in ES
idx = Index(es_index)
idx.delete()
def test_elasticsearch_origin(sdc_builder, sdc_executor, elasticsearch):
"""Test for Elasticsearch origin stage. We do so by putting data via Elastisearch client and reading via
Elastisearch origin pipeline. To assert, we will snapshot the pipeline.
The pipeline looks like:
Elasticsearch origin pipeline:
es_origin >> trash
"""
es_index = get_random_string(
string.ascii_letters,
10).lower() # Elasticsearch indexes must be lower case
es_doc_id = get_random_string(string.ascii_letters, 10)
raw_str = 'Hello World!'
builder = sdc_builder.get_pipeline_builder()
es_origin = builder.add_stage('Elasticsearch', type='origin')
es_origin.set_attributes(index=es_index,
query="{'query': {'match_all': {}}}")
trash = builder.add_stage('Trash')
es_origin >> trash
es_origin_pipeline = builder.build(
title='ES origin pipeline').configure_for_environment(elasticsearch)
sdc_executor.add_pipeline(es_origin_pipeline)
try:
# Put data to Elasticsearch
elasticsearch.connect()
doc_type = DocType(meta={'id': es_doc_id, 'index': es_index})
doc_type.body = raw_str
doc_type.save() # save document to Elasticsearch
index = Index(es_index)
assert index.refresh(
) # assert to refresh index, making all operations available for search
# Run pipeline and assert
snapshot = sdc_executor.capture_snapshot(es_origin_pipeline,
start_pipeline=True).snapshot
# no need to stop pipeline - as ES origin shuts off once data is read from Elasticsearch
snapshot_data = snapshot[
es_origin.instance_name].output[0].value['value']
# assert ES meta
assert snapshot_data['_index']['value'] == es_index and snapshot_data[
'_id']['value'] == es_doc_id
# assert ES data
assert snapshot_data['_source']['value']['body']['value'] == raw_str
finally:
# Clean up test data in ES
idx = Index(es_index)
idx.delete()
def test_elasticsearch_target_additional_properties(sdc_builder, sdc_executor, elasticsearch):
"""
Elasticsearch target pipeline, adding additional properties, where specifies every routing with the value of the
shard's record. It checks if the value of the record-label is added correctly to the property routing at
ElasticSearch query.
dev_raw_data_source >> es_target
"""
# Test static
index_values = []
for j in range(4):
index_values.append(get_random_string(string.ascii_letters, 10).lower())
raw_data = [{"text": "Record1", "index": index_values[0], "mapping": get_random_string(string.ascii_letters, 10).lower(),
"doc_id": get_random_string(string.ascii_letters, 10).lower(), "shard": "record1"},
{"text": "Record2", "index": index_values[1], "mapping": get_random_string(string.ascii_letters, 10).lower(),
"doc_id": get_random_string(string.ascii_letters, 10).lower(), "shard": "record2"},
{"text": "Record3", "index": index_values[2], "mapping": get_random_string(string.ascii_letters, 10).lower(),
"doc_id": get_random_string(string.ascii_letters, 10).lower(), "shard": "record3"},
{"text": "Record4", "index": index_values[3], "mapping": get_random_string(string.ascii_letters, 10).lower(),
"doc_id": get_random_string(string.ascii_letters, 10).lower(), "shard": None}]
# Build pipeline
builder = sdc_builder.get_pipeline_builder()
dev_raw_data_source = builder.add_stage('Dev Raw Data Source').set_attributes(data_format='JSON',
stop_after_first_batch=True,
raw_data='\n'.join(json.dumps(rec)
for rec in raw_data))
es_target = builder.add_stage('Elasticsearch', type='destination')
es_target.set_attributes(default_operation='INDEX', document_id='${record:value(\'/doc_id\')}',
index='${record:value(\'/index\')}', mapping='${record:value(\'/mapping\')}',
additional_properties='{\"_routing\":${record:value(\'/shard\')}}')
dev_raw_data_source >> es_target
es_target_pipeline = builder.build(title='ES target pipeline').configure_for_environment(elasticsearch)
sdc_executor.add_pipeline(es_target_pipeline)
try:
elasticsearch.connect()
# Make sure that the index exists properly before running the test
index = Index(index_values[0])
index.create()
assert index.refresh()
# Run pipeline with additional properties
sdc_executor.start_pipeline(es_target_pipeline).wait_for_finished()
es_response = []
for i in index_values:
es_search = ESSearch(index=i)
response = es_search.execute()
es_response.append(response[0])
time.sleep(5)
assert len(es_response) == 4
for r in es_response:
assert r
if r.text == "Record4":
for attribute in r.meta:
assert attribute != "routing"
else:
assert r.shard == r.meta.routing
finally:
# Clean up test data in ES
idx = Index(index_values[0])
idx.delete()