java - How long the messages will be kept stored in topic/partition using kafka 0.9 -


i'm using kafkaconsumer api fetch data topic (one partition per topic), after records has been retrieved poll method , processed, if new instance of kafkaconsumer created , try fetch data same topic/partition i'm able retrieve same data in first time. there way remove records topic/partition after has been consumed ?


Comments

Post a Comment

Popular posts from this blog

Receive udp packets in android gstreamer -

i using eclipse juno in windows 7. doing programming on android 4.2 platform. want receive udp packets in gstreamer application. giving uri udp://127.0.0.1:1234 , sending file vlc player same computer. emulator giving message could not get/set setting from/on resource while in case of rtp, giving message no uri implementer found rtp ideas how receive streaming media in android?
Read more

php - Extract Text from HTTP referer -

i using following code show referer link page on website. how can modify code shows part of link. i.e if website url www.example.com/?s=printing want extract printing. , should happen if format www.example.com/?s=aaa , not if format else www.example.com/printing. code: <?php session_start(); if ( !isset( $_session["origurl"] ) ) $_session["origurl"] = $_server["http_referer"]; echo $_session["origurl"] ?> i figured out , following code works: <?php session_start(); if ( !isset( $_session["origurl"] ) ) $_session["origurl"] = $_server["http_referer"]; $mysearchterm = $_server["http_referer"]; $whatiwant = substr($mysearchterm, strpos($mysearchterm, "=") +1); echo $whatiwant; ?>
Read more

matplotlib - PYTHON: Annotate boxes disapear dependant on range -

Image
i have issue plotting info boxes of data , fit. toy example follows. import numpy np import matplotlib.pyplot plt #works sigma = 0.12 mu = 0.5 #half works sigma = 0.1 mu = 0.3 ##none works #sigma = 0.05 #mu = 0.2 sample = np.random.normal(mu, sigma, 10000) fighs = plt.figure() axhs = fighs.add_subplot(1, 1, 1) n, histbins, patches = axhs.hist(sample,100, histtype='step', normed=1) axhs.annotate("$\mu=%.3f$ \n $\sigma=%.3f$ \n $n=%i$"% (sample.mean(), sample.std(), len(sample)), xytext=(0.8, 0.85), bbox=dict(boxstyle="sawtooth", fc="w"), xy=(0.8, 0.85), textcoords='axes fraction') axhs.plot(histbins, plt.mlab.normpdf(histbins, mu, sigma)) axhs.annotate(" $\mu=%.3f$ \n $\sigma=%.3f$ \n $n=%s$"%(mu,sigma,"--"), xytext=(0.6, 0.85), bbox=dict(boxstyle="round", fc="w"), xy=(0.6, 0.85), textcoords='axes fraction') plt....
Read more