Member since
12-21-2016
83
Posts
5
Kudos Received
2
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My Accepted Solutions
| Title | Views | Posted |
|---|---|---|
| 45741 | 02-08-2017 05:56 AM |
04-20-2020
03:17 PM
Hi, I am trying to connect from local machine to a kerberized kafka cluster through python as python client, could you please let me know what all the properties to include along with bootstrap server ? consumer = KafkaConsumer('test',bootstrap_servers='XXX.ORG:XXXX', #client_id= kafka-python- + __version__, request_timeout_ms=30000, connections_max_idle_ms=9 * 60 * 1000, reconnect_backoff_ms=50, reconnect_backoff_max_ms=1000, max_in_flight_requests_per_connection=5, receive_buffer_bytes=None, send_buffer_bytes=None, #socket_options= [(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)], sock_chunk_bytes=4096, # undocumented experimental option sock_chunk_buffer_count=1000, # undocumented experimental option retry_backoff_ms=100, metadata_max_age_ms=300000, security_protocol='SASL_SSL', ssl_context=None, ssl_check_hostname=True, ssl_cafile=None, ssl_certfile=None, ssl_keyfile=None, ssl_password=None, ssl_crlfile=None, api_version=None, api_version_auto_timeout_ms=2000, #selector=selectors.DefaultSelector, sasl_mechanism='GSSAPI', #sasl_plain_username= None, #sasl_plain_password='XXXX', sasl_kerberos_service_name='XXXX', # metrics configs metric_reporters=[], metrics_num_samples=2, metrics_sample_window_ms=30000) Your help is appreciated. Thanks
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04-20-2020
03:07 PM
Hi All, I am trying to connect from Local machine to kafka cluster(kerberized Cluster) through python. Can anyone help what are the properties to specify for the krb5.conf file and other properties. your help is appreciated.
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02-08-2017
05:56 AM
2 Kudos
Here is work around, which i have implemented. For an external table, If you are trying to drop a partition and as-well would like to delete the data. This can be achieved as below. 1. Alter external table as internal table -- by changing the TBL properties as external =false 2. Drop the partitions -- when you drop the partitions, data pertained to the partitions will also be dropped as now this table is managed table 3. Alter back the table as external=True. By doing this, there more controlled on what we are deleting and drop the partitions rather than using hadoop rm command
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